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CyberAlbSecOP/Awesome_GPT_Super_Prompting

ChatGPT Jailbreaks, GPT Assistants Prompt Leaks, GPTs Prompt Injection, LLM Prompt Security, Super Prompts, Prompt Hack, Prompt Security, Ai Prompt Engineering, Adversarial Machine Learning.

⭐⭐⭐⭐⭐ +3000 STARS | THANK YOU! ⭐⭐⭐⭐⭐

What will you find in V.2.0:

ChatGPT Jailbreaks
GPT Assistants Prompt Leaks
GPTs Prompt Injection
LLM Prompt Security
Super Prompts
Prompt Hack
Prompt Security
Ai Prompt Engineering
Adversarial Machine Learning

⚠️ Into "Latest Jailbreaks" folder, just check latest additions for working Jailbreaks. ⚠️
⚠️ If you find your secret prompts here and want it removed, please let me know ASAP. ⚠️

Legend:

🌟: Legendary!
🔥: Hot Stuff

Jailbreak Hall Of Fame:

🏆 | /elder-plinius
🏆 | u/yell0wfever92
🏆 | u/HORSELOCKSPACEPIRATE
🏆 | u/FamilyK1ng
🏆 | u/getoffmylawn0014
🏆 | u/Positive_Average_446

🚨 Jailbreaks

Explore techniques for bypassing restrictions on GPT models.

🌟 | r/ChatGPTJailbreak/ - Reddit community focused on ChatGPT jailbreaks.
🌟 | elder-plinius/L1B3RT45 - A repository for advanced jailbreak strategies.
🔥 | cyberark/FuzzyAI - A powerful tool for automated LLM fuzzing.
🔥 | verazuo/jailbreak_llms - Methods to jailbreak various large language models.
🔥 | rentry.org - Collection of various jailbreak prompts.
catsanzsh/01preview-jailbreaks - A collection of Jailbreaks for o1-preview.
yueliu1999/Awesome-Jailbreak-on-LLMs - A curated list of LLM jailbreak techniques.
0xk1h0/ChatGPT_DAN - Jailbreak prompts designed to activate the "DAN" mode in ChatGPT.
tg12/gpt_jailbreak_status - A tool for monitoring jailbreak status of GPT models.
Cyberlion-Technologies/ChatGPT_DAN - Another implementation of ChatGPT DAN mode prompts.
yes133/ChatGPT-Prompts-Jailbreaks-And-More - Collection of various jailbreak prompts.
THUDM/ChatGLM-6B - Collection of various jailbreak prompts.
GabryB03/ChatGPT-Jailbreaks - Repository with different ChatGPT jailbreak techniques.
jzzjackz/chatgptjailbreaks - A simple repository showcasing jailbreak attempts.
jackhhao/jailbreak-classification - Dataset for classifying jailbreak prompts.
rubend18/ChatGPT-Jailbreak-Prompts - A dataset of jailbreak prompts for ChatGPT.
deadbits/vigil-jailbreak-ada-002 - Vigilant dataset for ADA-002 jailbreak attempts.

🕵️‍♂️ GPT Agents System Prompt Leaks

Find leaked prompts and system information from GPT agents.

🌟 | 0xeb/TheBigPromptLibrary - Extensive library of system prompts for GPT agents.
🔥 | LouisShark/chatgpt_system_prompt - Collection of leaked system prompts for ChatGPT.
gogooing/Awesome-GPTs - A collection of useful GPT prompts.
tjadamlee/GPTs-prompts - Another repository with a variety of GPT prompts.
linexjlin/GPTs - Compilation of various GPT prompts.
B3o/GPTS-Prompt-Collection - A rich collection of GPT prompts.
1003715231/gptstore-prompts - Repository containing a store of GPT prompts.
friuns2/Leaked-GPTs - Leaked GPT system prompts repository.
adamidarrha/TopGptPrompts - Top GPT prompts curated from various sources.
friuns2/BlackFriday-GPTs-Prompts - Special edition leaked GPT prompts.
parmarjh/Leaked-GPTs - More leaked system prompts for GPT models.
lxfater/Awesome-GPTs - Awesome collection of GPT prompts.
Superdev0909/Awesome-AI-GPTs-main - A main repository for awesome GPT prompts.
SuperShinyDev/ChatGPTApplication - Application repository for GPT models with prompts.

🛡️ Prompt Injection

Resources focused on exploiting or defending against prompt injections.

🌟 | AnthenaMatrix - Comprehensive repository on prompt injection techniques.
🔥 | utkusen/promptmap - Tool for mapping and analyzing prompt injections.
🔥 | microsoft/promptbench - Benchmarking tool for prompt injection vulnerabilities.
Cranot/chatbot-injections-exploits - Repository of exploits based on prompt injections in chatbots.
FonduAI/awesome-prompt-injection - Awesome list of resources on prompt injection.
TakSec/Prompt-Injection-Everywhere - Guide to prompt injection in various systems.
yunwei37/prompt-hacker-collections - Collection of prompt hacking methods and exploits.
PromptTrace is a free, hands-on AI security training platform for practicing prompt injection, RAG poisoning, and tool exploitation against real LLMs.
AdverserialAttack-InjectionPrompt - Adversarial attacks through prompt injections.

🔐 Secure Prompting

Repositories dedicated to securing prompts and mitigating vulnerabilities.

🌟 | Valhall-ai/prompt-injection-mitigations - Mitigation strategies for prompt injections.
🔥 | cckuailong/awesome-gpt-security - A curated list of GPT security best practices.
onestardao/WFGY – 16 failure modes for RAG and agent pipelines (incl. prompt-injection patterns) with concrete mitigation checklists.
GPTGeeker/securityGPT - Security-focused prompts for GPT models.
mykeln/GPTect - GPT security protection techniques.
gavin-black-dsu/securePrompts - Repository with secure GPT prompts.
zinccat/PromptSafe - Ensuring safe prompts for GPT models.
BenderScript/PromptGuardian - Guardian scripts for securing GPT prompts.
sinanw/llm-security-prompt-injection - Security-focused prompt injection repository.

🗂️ GPTs Lists

Collections of various GPT resources and lists.

🌟 | EmbraceAGI/Awesome-AI-GPTs - Comprehensive list of AI and GPT resources.
🔥 | Anil-matcha/Awesome-GPT-Store - A store of awesome GPT prompts and resources.
AI/ML API - AI/ML API provides 300+ AI models including Deepseek, Gemini, ChatGPT.
gogooing/Awesome-GPTs - General collection of GPT-related resources.
friuns2/Awesome-GPTs-Big-List - Big list of awesome GPT prompts and tools.
AgentOps-AI/BestGPTs - Compilation of the best GPT resources.
fr0gger/Awesome-GPT-Agents - Focused on GPT agents and their capabilities.
cckuailong/awesome-gpt-security - Security-centric GPT resources.
LiLittleCat/awesome-free-chatgpt/tree - List of free ChatGPT mirror sites, continuously updated.
cheahjs/free-llm-api-resources - A list of free LLM inference resources accessible via API.
sindresorhus/awesome-chatgpt - Awesome list for ChatGPT — an artificial intelligence chatbot developed by OpenAI.

📚 Prompts Libraries

Explore libraries of GPT prompts for various applications.

🌟 | ai-boost/awesome-prompts - A vast library of awesome GPT prompts.
🔥 | B3o/GPTS-Prompt-Collection - Extensive collection of prompts for GPT models.
abilzerian/LLM-Prompt-Library - Library of prompts for large language models.
f/awesome-chatgpt-prompts
yunwei37/prompt-hacker-collections - Collection of hacking-oriented GPT prompts.
alphatrait/100000-ai-prompts-by-contentifyai - Massive collection of AI prompts.
DummyKitty/Cyber-Security-chatGPT-prompt - Security-focused ChatGPT prompt library.
thepromptindex.com - Online index of GPT prompts.
snackprompt.com/ - A snackable collection of GPT prompts.
usethisprompt.io/ - A website to find and share GPT prompts.
promptbase.com/ - Marketplace for buying and selling GPT prompts.
prompts.chat/ - World's First & Most Famous Prompts Directory.

🛠️ Prompt Engineering

Resources to master the craft of prompt engineering.

🌟 | snwfdhmp/awesome-gpt-prompt-engineering - A list of awesome resources on prompt engineering.
🔥 | promptslab/Awesome-Prompt-Engineering - Another excellent list of prompt engineering resources.
NirDiamant/Prompt_Engineering - Comprehensive collection of tutorials and implementations for Prompt Engineering techniques
circlestarzero/HackOpenAISystemPrompts - Hacking OpenAI system prompts.
dair-ai/Prompt-Engineering-Guide - A guide to mastering prompt engineering.
brexhq/prompt-engineering - Comprehensive resource for prompt engineering.
natnew/Awesome-Prompt-Engineering - More resources on awesome prompt engineering.
Agent Shadow Brain - Self-evolving AI coding intelligence with infinite memory (TurboQuant), genetic algorithm self-evolution, predictive bug detection, PageRank knowledge graphs, swarm intelligence, and adversarial defense.
Omni Skills Forge - 50,000+ curated AI agent skills for Claude Code, Cursor, Copilot, Windsurf, Cline. Visual dashboard, one-click install, skill doctor, auto-update.
promptingguide.ai - An online guide to prompt engineering.
promptdev.ai - Platform for developing and sharing prompts.
learnprompting.org - Learn the art of prompting from scratch.
learningprompt.wiki/ - Free Prompt Engineering Online Course.

🔎 Prompt Sources

Communities and forums for discovering and sharing prompts.

🌟 | r/ChatGPTJailbreak/ - Reddit community for ChatGPT jailbreaks.
🔥 | r/ChatGPTPromptGenius/ - Subreddit for sharing and discovering GPT prompts.
r/chatgpt_promptDesign/ - Focused on designing effective ChatGPT prompts.
r/PromptEngineering/ - Subreddit dedicated to prompt engineering discussions.
r/PromptDesign/ - Community for prompt design.
r/GPT_jailbreaks/ - Discussion on GPT jailbreak methods.
r/ChatGptDAN/ - Community for DAN mode and ChatGPT jailbreaks.
r/PromptSharing/ - Share and discover prompts with the community.
r/PromptWizardry/ - Subreddit for creative and advanced prompting.
r/PromptWizards/ - Community for wizards of prompt engineering.
altenens.is/forums/chatgpt-tools - Forum for sharing GPT tools and resources.
onehack.us/prompt - Another platform for discovering GPT prompts.
God Tier Prompts - A community driven leaderboard where the best prompts rise to the top.

⚙️ Ai Automation Tools

Tools to create AI Automations.

make.com - Connect any app, data source, or AI model. Build and manage automations and AI agents – visually, in code, or with a prompt.
patl4588/metercall-launch - The new layer of the internet. 21M APIs. 727 modules. One prompt.

🧠 Cyber-Albsecop GPT Agents

Specialized GPT agents focused on cybersecurity and more.

ALBSECOP | Cyber Security Master - GPT agent for mastering cybersecurity.
VAMPIRE | Ultra Prompt Writer - GPT agent specializing in writing ultra-effective prompts.
ORK | Super Prompt Optimizer - GPT agent for optimizing prompts.
MINOTAUR | Impossible Security Challenge! - A GPT agent offering challenging security tasks.
KEVLAR | Anti-Leak System Prompts - Agent designed to create anti-leak system prompts.

To do for V3.00

Keep the repo updated and hot
Add more personal prompts
Add more external sources
Add instruction on how to use prompts

Star History

Keywords:

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trycua/cua

Open-source infrastructure for Computer-Use Agents. Sandboxes, SDKs, and benchmarks to train and evaluate AI agents that can control full desktops (macOS, Linux, Windows).

Build, benchmark, and deploy agents that use computers

Choose Your Path

Cua Driver - Background computer-use on macOS

Drive any native macOS app in the background — agents click, type, and verify without stealing the cursor, focus, or Space, even on non-AX surfaces like Chromium web content and canvas-based tools (Blender, Figma, DAWs, game engines). Use with the CLI or MCP server for Claude Code, Cursor, and custom clients. Every session records as a replayable trajectory.

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/cua-driver/scripts/install.sh)"

Full tool reference, architecture notes, and the Claude Code skill ship with the package: libs/cua-driver/README.md.

Cua - Agent-Ready Sandboxes for Any OS

Build agents that see screens, click buttons, and complete tasks autonomously. One API for any VM or container image — cloud or local.

pip install cua

# Requires Python 3.11 or later
from cua import Sandbox, Image

# Same API regardless of OS or runtime
async with Sandbox.ephemeral(Image.linux()) as sb:   # or .macos() .windows() .android()
    result = await sb.shell.run("echo hello")
    screenshot = await sb.screenshot()
    await sb.mouse.click(100, 200)
    await sb.keyboard.type("Hello from Cua!")
    await sb.mobile.gesture((100, 500), (100, 200))  # multi-touch gestures

	Linux container	Linux VM	macOS	Windows	Android	BYOI (.qcow2, .iso)
Cloud (cua.ai)	✅	✅	✅	✅	✅	🔜 soon
Local (QEMU)	✅	✅	✅	✅	✅	✅

Get Started | Examples | API Reference

CuaBot - Co-op computer-use for any agent

cuabot gives any coding agent a seamless sandbox for computer-use. Individual windows appear natively on your desktop with H.265, shared clipboard, and audio.

npx cuabot                 # Setup onboarding

# Run any agent in a sandbox
cuabot claude              # Claude Code
cuabot openclaw            # OpenClaw in the sandbox

# Run any GUI workflow in a sandbox
cuabot chromium
cuabot --screenshot
cuabot --type "hello"
cuabot --click <x> <y> [button]

Built-in support for agent-browser and agent-device (iOS, Android) out of the box.

Get Started | Installation | First spotted at ClawCon

Cua-Bench - Benchmarks & RL Environments

Evaluate computer-use agents on OSWorld, ScreenSpot, Windows Arena, and custom tasks. Export trajectories for training.

# Install and create base image
cd cua-bench
uv tool install -e . && cb image create linux-docker

# Run benchmark with agent
cb run dataset datasets/cua-bench-basic --agent cua-agent --max-parallel 4

Get Started | Partner With Us | Registry | CLI Reference

Lume - macOS Virtualization

Create and manage macOS/Linux VMs with near-native performance on Apple Silicon using Apple's Virtualization.Framework.

# Install Lume
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/trycua/cua/main/libs/lume/scripts/install.sh)"

# Pull & start a macOS VM
lume run macos-sequoia-vanilla:latest

Get Started | FAQ | CLI Reference

Packages

Package	Description
cuabot	Multi-agent computer-use sandbox CLI
cua-agent	AI agent framework for computer-use tasks
cua-sandbox	SDK for creating and controlling sandboxes
cua-computer-server	Driver for UI interactions and code execution in sandboxes
cua-bench	Benchmarks and RL environments for computer-use
lume	macOS/Linux VM management on Apple Silicon
lumier	Docker-compatible interface for Lume VMs

Resources

Documentation — Guides, examples, and API reference
Blog — Tutorials, updates, and research
Discord — Community support and discussions
GitHub Issues — Bug reports and feature requests

Contributing

We welcome contributions! See our Contributing Guidelines for details.

License

MIT License — see LICENSE for details.

Third-party components have their own licenses:

Kasm (MIT)
OmniParser (CC-BY-4.0)
Optional cua-agent[omni] includes ultralytics (AGPL-3.0)

Trademarks

Apple, macOS, Ubuntu, Canonical, and Microsoft are trademarks of their respective owners. This project is not affiliated with or endorsed by these companies.

Thank you to all our GitHub Sponsors!

wilsonfreitas/awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

Awesome Quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance).

Numerical Libraries & Data Structures

numpy - Python - NumPy is the fundamental package for scientific computing with Python. GitHub
scipy - Python - SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. GitHub
pandas - Python - pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. GitHub
polars - Python - Polars is a blazingly fast DataFrame library for manipulating structured data. GitHub
quantdsl - Python - Domain specific language for quantitative analytics in finance and trading.
statistics - Python - Builtin Python library for all basic statistical calculations.
sympy - Python - SymPy is a Python library for symbolic mathematics. GitHub
pymc3 - Python - Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano. GitHub
modelx - Python - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas. GitHub
ArcticDB - Python - High performance datastore for time series and tick data.
CRNG - Python - Contingency Random Number Generator that produces random numbers with real financial market statistical signatures (fat tails, volatility clustering, kurtosis). Matches 86% of real market metrics vs 14% for NumPy.
xts - R - eXtensible Time Series: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
data.table - R - Extension of data.frame: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns and a fast file reader (fread). Offers a natural and flexible syntax, for faster development.
sparseEigen - R - Sparse principal component analysis.
TSdbi - R - Provides a common interface to time series databases.
tseries - R - Time Series Analysis and Computational Finance.
zoo - R - S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations).
tis - R - Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
tfplot - R - Utilities for simple manipulation and quick plotting of time series data.
tframe - R - A kernel of functions for programming time series methods in a way that is relatively independently of the representation of time.
Temporal.jl - Julia - Flexible and efficient time series class & methods.
DataFrames.jl - Julia - In-memory tabular data in Julia.
TSFrames.jl - Julia - Handle timeseries data on top of the powerful and mature DataFrames.jl.
TimeArrays.jl - Julia - Time series handling for Julia.

Financial Instruments & Pricing

PyQL - Python - QuantLib's Python port.
pyfin - Python - Basic options pricing in Python. ARCHIVED.
vollib - Python - vollib is a python library for calculating option prices, implied volatility and greeks.
QuantPy - Python - A framework for quantitative finance In python.
Finance-Python - Python - Python tools for Finance.
ffn - Python - A financial function library for Python.
pynance - Python - Lightweight Python library for assembling and analyzing financial data.
tia - Python - Toolkit for integration and analysis.
pysabr - Python - SABR model Python implementation.
FinancePy - Python - A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
gs-quant - Python - Python toolkit for quantitative finance.
willowtree - Python - Robust and flexible Python implementation of the willow tree lattice for derivatives pricing.
financial-engineering - Python - Applications of Monte Carlo methods to financial engineering projects, in Python.
optlib - Python - A library for financial options pricing written in Python.
tf-quant-finance - Python - High-performance TensorFlow library for quantitative finance.
Q-Fin - Python - A Python library for mathematical finance.
Quantsbin - Python - Tools for pricing and plotting of vanilla option prices, greeks and various other analysis around them.
finoptions - Python - Complete python implementation of R package fOptions with partial implementation of fExoticOptions for pricing various options.
pypme - Python - PME (Public Market Equivalent) calculation.
AbsBox - Python - A Python based library to model cashflow for structured product like Asset-backed securities (ABS) and Mortgage-backed securities (MBS).
Intrinsic-Value-Calculator - Python - A Python tool for quick calculations of a stock's fair value using Discounted Cash Flow analysis.
Kelly-Criterion - Python - Kelly Criterion implemented in Python to size portfolios based on J. L. Kelly Jr's formula.
rateslib - Python - A fixed income library for pricing bonds and bond futures, and derivatives such as IRS, cross-currency and FX swaps.
fypy - Python - Vanilla and exotic option pricing library to support quantitative R&D. Focus on pricing interesting/useful models and contracts (including and beyond Black-Scholes), as well as calibration of financial models to market data.
Pyderivatives - Python - Toolkit for option pricing, implied volatility surfaces, risk-neutral densities, and pricing kernel surfaces with support for advanced models including Heston, Kou, and Bates.
quantra - Python - High-performance pricing engine built on QuantLib. It exposes QuantLib's functionality through gRPC and REST APIs, enabling distributed computations with FlatBuffers serialization.
optionlab - Python - A Python library for evaluating option trading strategies.
flashalpha - Python - Python client for the FlashAlpha options analytics API.
QuantOracle - Python - Free quant finance API with 63 deterministic endpoints for options pricing, risk analysis, portfolio optimization, Monte Carlo simulation, and technical indicators.
RQuantLib - R - RQuantLib connects GNU R with QuantLib.
quantmod - R - Quantitative Financial Modelling Framework. GitHub
Rmetrics - R - The premier open source software solution for teaching and training quantitative finance.
- fAsianOptions - EBM and Asian Option Valuation.
- fAssets - Analysing and Modelling Financial Assets.
- fBasics - Markets and Basic Statistics.
- fBonds - Bonds and Interest Rate Models.
- fExoticOptions - Exotic Option Valuation.
- fOptions - Pricing and Evaluating Basic Options.
- fPortfolio - Portfolio Selection and Optimization.
sde - R - Simulation and Inference for Stochastic Differential Equations.
YieldCurve - R - Modelling and estimation of the yield curve.
SmithWilsonYieldCurve - R - Constructs a yield curve by the Smith-Wilson method from a table of LIBOR and SWAP rates.
ycinterextra - R - Yield curve or zero-coupon prices interpolation and extrapolation.
AmericanCallOpt - R - This package includes pricing function for selected American call options with underlying assets that generate payouts.
VarSwapPrice - R - Pricing a variance swap on an equity index.
RND - R - Risk Neutral Density Extraction Package.
LSMonteCarlo - R - American options pricing with Least Squares Monte Carlo method.
OptHedging - R - Estimation of value and hedging strategy of call and put options.
tvm - R - Time Value of Money Functions.
OptionPricing - R - Option Pricing with Efficient Simulation Algorithms.
credule - R - Credit Default Swap Functions.
derivmkts - R - Functions and R Code to Accompany Derivatives Markets. GitHub
FinCal - R - Package for time value of money calculation, time series analysis and computational finance.
r-quant - R - R code for quantitative analysis in finance.
options.studies - R - options trading studies functions for use with options.data package and shiny.
fmbasics - R - Financial Market Building Blocks.
R-fixedincome - R - Fixed income tools for R.
QuantLib.jl - Julia - Quantlib implementation in pure Julia.
Ito.jl - Julia - A Julia package for quantitative finance.
Miletus.jl - Julia - A financial contract definition, modeling language, and valuation framework.
Strata - Java - Modern open-source analytics and market risk library designed and written in Java. GitHub
JQuantLib - Java - JQuantLib is a free, open-source, comprehensive framework for quantitative finance, written in 100% Java.
finmath.net - Java - Java library with algorithms and methodologies related to mathematical finance. GitHub
quantcomponents - Java - Free Java components for Quantitative Finance and Algorithmic Trading.
DRIP - Java - Fixed Income, Asset Allocation, Transaction Cost Analysis, XVA Metrics Libraries.
finance.js - JavaScript - A JavaScript library for common financial calculations.
quantfin - Haskell - quant finance in pure haskell.
Haxcel - Haskell - Excel Addin for Haskell.
Ffinar - Haskell - A financial maths library in Haskell.
QuantScale - Scala - Scala Quantitative Finance Library.
Scala Quant - Scala - Scala library for working with stock data from IFTTT recipes or Google Finance.
QuantMath - Rust - Financial maths library for risk-neutral pricing and risk.
RustQuant - Rust - Quantitative finance library written in Rust.
QoX - Python - Finite difference pricing library written in Rust.

Technical Indicators

pandas_talib - Python - A Python Pandas implementation of technical analysis indicators.
finta - Python - Common financial technical analysis indicators implemented in Pandas.
Tulipy - Python - Financial Technical Analysis Indicator Library (Python bindings for tulipindicators).
lppls - Python - A Python module for fitting the Log-Periodic Power Law Singularity (LPPLS) model.
talipp - Python - Incremental technical analysis library for Python.
streaming_indicators - Python - A python library for computing technical analysis indicators on streaming data.
TA-Lib - Python - Python wrapper for TA-Lib (http://ta-lib.org/).
ta - Python - Technical Analysis Library using Pandas (Python).
bta-lib - Python - Technical Analysis library in pandas for backtesting algotrading and quantitative analysis.
TuneTA - Python - TuneTA optimizes technical indicators using a distance correlation measure to a user defined target feature such as next day return.
TTR - R - Technical Trading Rules.
TALib.jl - Julia - A Julia wrapper for TA-Lib.
Indicators.jl - Julia - Financial market technical analysis & indicators on top of Temporal.
TechnicalIndicatorCharts.jl - Julia - Visualize OnlineTechnicalIndicators.jl using LightweightCharts.jl.
MarketTechnicals.jl - Julia - Technical analysis of financial time series on top of TimeSeries.
OnlineTechnicalIndicators.jl - Julia - Julia Technical Analysis Indicators via online algorithms.
ta4j - Java - A Java library for technical analysis.
IndicatorTS - JavaScript - Indicator is a TypeScript module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.
chart-patterns - JavaScript - Technical analysis library for Market Profile, Volume Profile, Stacked Imbalances and High Volume Node indicators.
orderflow - JavaScript - Orderflow trade aggregator for building Footprint Candles from exchange websocket data.
IndicatorGo - Golang - IndicatorGo is a Golang module providing various stock technical analysis indicators, strategies, and a backtest framework for trading.
TradeAggregation - Rust - Aggregate trades into user-defined candles using information driven rules.
SlidingFeatures - Rust - Chainable tree-like sliding windows for signal processing and technical analysis.
fin-primitives - Rust - Financial market primitives in Rust: Price/Quantity/Symbol newtypes, BTreeMap order book, OHLCV aggregation, SMA/EMA/RSI indicators, position ledger with PnL, and composable risk monitor.

Trading & Backtesting

income-desk - Python - Systematic options trading intelligence for small accounts with desk-based portfolio management, pre-trade validation, and multi-broker consolidation.
AI Quant Agents - Python - Multi-agent LLM trading analysis where 12 AI agents (analysts, debaters, risk manager) debate stock picks in real-time, supporting US equities and China A-shares.
TradeSight - Python - Self-hosted AI trading platform with strategy evolution, technical analysis, backtesting, and paper trading via Alpaca.
Orallexa - Python - AI trading operating system with 9 ML models (RF, XGBoost, EMAformer, MOIRAI-2, Chronos-2, DDPM, PPO RL, GNN, LR) ranked by Sharpe ratio, Claude AI synthesis with dual-tier routing (~$0.003/analysis), real-time Next.js dashboard, Alpaca paper trading, and 277 automated tests.
Vibe-Trading - Python - Natural-language multi-agent finance research agent with 29 swarm presets, 70 skills, and 28 auto-discovered tools; 7 backtest engines covering A-shares/US/Crypto/Futures/Forex/Options plus a cross-market CompositeEngine with shared capital pool; 5-source auto-fallback data layer (tushare/okx/yfinance/akshare/ccxt); 17-tool MCP server; includes trade-journal behavioral diagnostics for 同花顺/东财/富途 exports.
DeepAlpha - Python - AI crypto trading bot for Bybit with 70.9% walk-forward validated accuracy on out-of-sample data, LightGBM + XGBoost ensemble with 72 ML features. GitHub
the0 - Python - Self-hosted execution engine for algorithmic trading bots. Write strategies in Python, TypeScript, Rust, C++, C#, Scala, or Haskell and deploy with one command. Each bot runs in an isolated container with scheduled or streaming execution.
Investing algorithm framework - Python - Framework for developing, backtesting, and deploying automated trading algorithms.
Lumibot - Python - Algorithmic trading framework where the same code runs for backtesting and live trading across stocks, options, crypto, futures, and forex with multiple brokers including Alpaca, Interactive Brokers, Tradier, and Schwab.
QSTrader - Python - QSTrader backtesting simulation engine.
Blankly - Python - Fully integrated backtesting, paper trading, and live deployment.
zipline - Python - Pythonic algorithmic trading library.
zipline-reloaded - Python - Zipline, a Pythonic Algorithmic Trading Library.
QuantSoftware Toolkit - Python - Python-based open source software framework designed to support portfolio construction and management.
quantitative - Python - Quantitative finance, and backtesting library.
analyzer - Python - Python framework for real-time financial and backtesting trading strategies.
bt - Python - Flexible Backtesting for Python.
backtrader - Python - Python Backtesting library for trading strategies.
pythalesians - Python - Python library to backtest trading strategies, plot charts, seamlessly download market data, analyze market patterns etc.
pybacktest - Python - Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier.
pyalgotrade - Python - Python Algorithmic Trading Library.
basana - Python - A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.
algobroker - Python - This is an execution engine for algo trading.
finmarketpy - Python - Python library for backtesting trading strategies and analyzing financial markets.
binary-martingale - Python - Computer program to automatically trade binary options martingale style.
fooltrader - Python - the project using big-data technology to provide an uniform way to analyze the whole market.
zvt - Python - the project using sql, pandas to provide an uniform and extendable way to record data, computing factors, select securities, backtesting, realtime trading and it could show all of them in clearly charts in realtime.
pylivetrader - Python - zipline-compatible live trading library.
pipeline-live - Python - zipline's pipeline capability with IEX for live trading.
zipline-extensions - Python - Zipline extensions and adapters for QuantRocket.
moonshot - Python - Vectorized backtester and trading engine for QuantRocket based on Pandas.
pyqstrat - Python - A fast, extensible, transparent python library for backtesting quantitative strategies.
NowTrade - Python - Python library for backtesting technical/mechanical strategies in the stock and currency markets.
pinkfish - Python - A backtester and spreadsheet library for security analysis.
PRISM-INSIGHT - Python - AI-powered stock analysis system with 13 specialized agents, automated trading via KIS API, supporting Korean & US markets.
FinClaw - Python - AI-powered financial intelligence engine with 8 master strategies across US, CN, and HK markets. Multi-agent architecture with +29.1% annual alpha. 227 tests.
aat - Python - Async Algorithmic Trading Engine.
Backtesting.py - Python - Backtest trading strategies in Python.
catalyst - Python - An Algorithmic Trading Library for Crypto-Assets in Python.
quantstats - Python - Portfolio analytics for quants, written in Python.
jquantstats - Python - Modern variation of quantstats, with additional features and performance improvements.
qtpylib - Python - QTPyLib, Pythonic Algorithmic Trading http://qtpylib.io.
Quantdom - Python - Python-based framework for backtesting trading strategies & analyzing financial markets [GUI ).]
freqtrade - Python - Free, open source crypto trading bot.
algorithmic-trading-with-python - Python - Free pandas and scikit-learn resources for trading simulation, backtesting, and machine learning on financial data.
Qlib - Python - An AI-oriented Quantitative Investment Platform by Microsoft. Full ML pipeline of data processing, model training, back-testing; and covers the entire chain of quantitative investment: alpha seeking, risk modeling, portfolio optimization, and order execution.
machine-learning-for-trading - Python - Code and resources for Machine Learning for Algorithmic Trading.
AlphaPy - Python - Automated Machine Learning [AutoML] with Python, scikit-learn, Keras, XGBoost, LightGBM, and CatBoost.
jesse - Python - An advanced crypto trading bot written in Python.
rqalpha - Python - A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities.
FinRL-Library - Python - A Deep Reinforcement Learning Library for Automated Trading in Quantitative Finance. NeurIPS 2020.
bulbea - Python - Deep Learning based Python Library for Stock Market Prediction and Modelling.
ib_nope - Python - Automated trading system for NOPE strategy over IBKR TWS.
OctoBot - Python - Open source cryptocurrency trading bot for high frequency, arbitrage, TA and social trading with an advanced web interface.
OpenFinClaw - Python Rust - AI-native hedge fund platform: natural language strategy generation, Rust backtesting engine, multi-market execution, and self-evolving strategy pipeline with community leaderboard.
Stock-Prediction-Models - Python - Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations.
AutoTrader - Python - A Python-based development platform for automated trading systems - from backtesting to optimization to livetrading.
fast-trade - Python - A library built with backtest portability and performance in mind for backtest trading strategies.
qf-lib - Python - QF-Lib is a Python library that provides high quality tools for quantitative finance.
tda-api - Python - Gather data and trade equities, options, and ETFs via TDAmeritrade.
vectorbt - Python - Find your trading edge, using a powerful toolkit for backtesting, algorithmic trading, and research.
Lean - Python C# - Lean Algorithmic Trading Engine by QuantConnect (Python, C#).
pysystemtrade - Python - pysystemtrade is the open source version of Robert Carver's backtesting and trading engine that implements systems according to the framework outlined in his book "Systematic Trading", which is further developed on his blog.
pytrendseries - Python - Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater.
PyLOB - Python - Fully functioning fast Limit Order Book written in Python.
PyBroker - Python - Algorithmic Trading with Machine Learning.
OctoBot Script - Python - A quant framework to create cryptocurrencies strategies - from backtesting to optimization to livetrading.
hftbacktest - Python - A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
vnpy - Python - VeighNa is a Python-based open source quantitative trading system development framework.
Intelligent Trading Bot - Python - Automatically generating signals and trading based on machine learning and feature engineering.
fastquant - Python - fastquant allows you to easily backtest investment strategies with as few as 3 lines of python code.
nautilus_trader - Python Rust - A high-performance algorithmic trading platform and event-driven backtester.
YABTE - Python - Yet Another (Python) BackTesting Engine.
Trading Strategy - Python - TradingStrategy.ai is a market data, backtesting, live trading and investor management framework for decentralised finance.
Hikyuu - Python C++ - A base on Python/C++ open source high-performance quant framework for faster analysis and backtesting, contains the complete trading system components for reuse and combination.
rust_bt - Python - A high performance, low-latency backtesting engine for testing quantitative trading strategies on historical and live data in Rust.
Gunbot Quant - Python - Toolkit for quantitative trading analysis. It integrates an advanced market screener, a multi-strategy, multi-asset backtesting engine. Use with built-in GUI or through CLI.
StrateQueue - Python - An open‑source, broker‑agnostic Python library that lets you seamlessly deploy strategies from any major backtesting engine to live (or paper) trading with zero code changes and built‑in safety controls.
PythonTradingFramework - Python - Python algorithmic trading bot framework for Kubernetes: backtesting, hyperparameter optimization, 150+ technical analysis indicators (RSI, MACD, Bollinger Bands, ADX), portfolio management, PostgreSQL integration, Helm deployment, CronJob scheduling. Minimal overhead, production-ready, Yahoo Finance data.
QTradeX-AI-Agents - Python - Example strategies for the QTradeX platfrom.
QTradeX-Algo-Trading-SDK - Python - AI-powered SDK featuring algorithmic trading, backtesting, deployment on 100+ exchanges, and multiple optimization engines.
antback - Python - A lightweight, event-loop-style backtest engine that allows a function-driven imperative style using efficient stateful helper functions and data containers.
VARRD - Python - AI-powered trading edge discovery platform that validates trading ideas with event studies, statistical tests, and real market data. Web app, MCP server, CLI (pip install varrd), and Python SDK.
JIT-Optimization-Engine - Python - High-performance analytical core using LLVM JIT (Numba) to process large-scale telemetry for quant diagnostics.
backtester-mcp - Python - Local-first backtesting engine with built-in overfitting checks (PBO, deflated Sharpe, bootstrap CI, walk-forward) and a native MCP server for AI agents. GitHub
backtest - R - Exploring Portfolio-Based Conjectures About Financial Instruments.
pa - R - Performance Attribution for Equity Portfolios.
QuantTools - R - Enhanced Quantitative Trading Modelling.
blotter - R - Transaction infrastructure for defining instruments, transactions, portfolios and accounts for trading systems and simulation. Provides portfolio support for multi-asset class and multi-currency portfolios. Actively maintained and developed.
quantstrat - R - Transaction-oriented infrastructure for constructing trading systems and simulation. Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.
QUANTAXIS - Matlab - Integrated Quantitative Toolbox with Matlab.
PROJ_Option_Pricing_Matlab - Matlab - Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader.
Fastback.jl - Julia - Blazing fast Julia backtester.
Lucky.jl - Julia - Modular, asynchronous trading engine in pure Julia.
Strategems.jl - Julia - Quantitative systematic trading strategy development and backtesting.
ccxt - JavaScript Python PHP - A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges.
TradeClaw - JavaScript - Open-source AI trading signal platform with RSI/MACD/EMA confluence scoring, real-time signals for 10+ assets, self-hostable with one Docker command.
Jiji - Ruby - Open Source Forex algorithmic trading framework using OANDA REST API.
Tai - Elixir/Erlang - Open Source composable, real time, market data and trade execution toolkit.
Workbench - Elixir/Erlang - From Idea to Execution - Manage your trading operation across a globally distributed cluster.
Prop - Elixir/Erlang - An open and opinionated trading platform using productive & familiar open source libraries and tools for strategy research, execution and operation.
Kelp - Golang - Kelp is an open-source Golang algorithmic cryptocurrency trading bot that runs on centralized exchanges and Stellar DEX (command-line usage and desktop GUI).
TradeFrame - CPP - C++ 17 based framework/library (with sample applications) for testing options based automated trading ideas using DTN IQ real time data feed and Interactive Brokers (TWS API) for trade execution. Comes with built-in Option Greeks/IV calculation library.
Hikyuu - Python C++ - A base on Python/C++ open source high-performance quant framework for faster analysis and backtesting, contains the complete trading system components for reuse and combination. You can use python or c++ freely.
OrderMatchingEngine - CPP - A production-grade, lock-free, high-frequency trading matching engine achieving 150M+ orders/sec.
PandoraTrader - CPP - A C++ CTP trading framework, with very clear logic.
NexusFix - CPP - C++23 FIX protocol engine with zero-copy parsing and SIMD acceleration, 3x faster than QuickFIX.
QuantConnect - CSharp - Lean Engine is an open-source fully managed C# algorithmic trading engine built for desktop and cloud usage.
StockSharp - CSharp - Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
TDAmeritrade.DotNetCore - CSharp - Free, open-source .NET Client for the TD Ameritrade Trading Platform. Helps developers integrate TD Ameritrade API into custom trading solutions.
Barter - Rust - Open-source Rust framework for building event-driven live-trading & backtesting systems.
LFEST - Rust - Simulated perpetual futures exchange to trade your strategy against.
OpenFinClaw - Python Rust - AI-native one-person hedge fund platform with Rust trading engine. Natural language → strategy → backtest → execution in 60s. Multi-market (US/HK/CN/Crypto), self-evolving strategy pipeline. Built on OpenClaw (68K+ stars).
Sextant - Python - Local event-driven backtesting engine with no-code strategy builder and FRED vintage, ALFRED, yFinance support.
TradeClaw - Node.js TypeScript - Open-source self-hosted AI trading signal platform. Generates buy/sell signals using RSI, MACD, EMA, Bollinger Bands for forex, crypto and commodities. Deployable via Docker Compose. (Demo)

Portfolio Optimization & Risk Analysis

skfolio - Python - Python library for portfolio optimization built on top of scikit-learn. It provides a unified interface and sklearn compatible tools to build, tune and cross-validate portfolio models.
PyPortfolioOpt - Python - Financial portfolio optimization in python, including classical efficient frontier and advanced methods.
Eiten - Python - Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic investing strategies such as Eigen Portfolios, Minimum Variance Portfolios, Maximum Sharpe Ratio Portfolios, and Genetic Algorithms based Portfolios.
riskparity.py - Python - fast and scalable design of risk parity portfolios with TensorFlow 2.0.
mlfinlab - Python - Implementations regarding "Advances in Financial Machine Learning" by Marcos Lopez de Prado. (Feature Engineering, Financial Data Structures, Meta-Labeling).
DeepDow - Python - Portfolio optimization with deep learning.
QuantLibRisks - Python - Fast risks with QuantLib.
XAD - Python - Automatic Differentation (AAD) Library.
pyfolio - Python - Portfolio and risk analytics in Python.
empyrical - Python - Common financial risk and performance metrics.
fecon235 - Python - Computational tools for financial economics include: Gaussian Mixture model of leptokurtotic risk, adaptive Boltzmann portfolios.
finance - Python - Financial Risk Calculations. Optimized for ease of use through class construction and operator overload.
qfrm - Python - Quantitative Financial Risk Management: awesome OOP tools for measuring, managing and visualizing risk of financial instruments and portfolios. (Last updated: 2015-12-12).
visualize-wealth - Python - Portfolio construction and quantitative analysis.
VisualPortfolio - Python - This tool is used to visualize the performance of a portfolio.
universal-portfolios - Python - Collection of algorithms for online portfolio selection.
FinQuant - Python - A program for financial portfolio management, analysis and optimization.
Empyrial - Python - Portfolio's risk and performance analytics and returns predictions.
risktools - Python - Risk tools for use within the crude and crude products trading space with partial implementation of R's PerformanceAnalytics.
Riskfolio-Lib - Python - Portfolio Optimization and Quantitative Strategic Asset Allocation in Python.
empyrical-reloaded - Python - Common financial risk and performance metrics. empyrical fork.
pyfolio-reloaded - Python - Portfolio and risk analytics in Python. pyfolio fork.
fortitudo.tech - Python - Conditional Value-at-Risk (CVaR) portfolio optimization and Entropy Pooling views / stress-testing in Python.
quantitative-finance-tools - Python - Library for portfolio optimization (MVO) and rigorous risk metrics (VaR/CVaR).
curistat - Python - Futures volatility forecasting platform for ES/NQ. Proprietary CVN rating (1-10), regime detection (CRC composite), 8 directional signals, economic event impact analytics. Includes MCP server for AI agent integration.
Prop Trader Compass - Python - Interactive risk and payout calculator for Futures and CFD traders; features one-time fee firm comparisons.
portfolio - R - Analysing equity portfolios.
sparseIndexTracking - R - Portfolio design to track an index.
riskParityPortfolio - R - Blazingly fast design of risk parity portfolios.
PortfolioAnalytics - R - Portfolio Analysis, Including Numerical Methods for Optimizationof Portfolios.
PerformanceAnalytics - R - Econometric tools for performance and risk analysis.
OnlinePortfolioAnalytics.jl - Julia - A Julia quantitative portfolio analytics (risk / performance) via online algorithms.
RiskPerf.jl - Julia - Quantitative risk and performance analysis package for financial time series powered by the Julia language.
portfolio-allocation - JavaScript - PortfolioAllocation is a JavaScript library designed to help constructing financial portfolios made of several assets: bonds, commodities, cryptocurrencies, currencies, exchange traded funds (ETFs), mutual funds, stocks...
Ghostfolio - JavaScript - Wealth management software to keep track of financial assets like stocks, ETFs or cryptocurrencies and make solid, data-driven investment decisions.
rebalance - JavaScript - Interactive portfolio rebalancing tool that imports brokerage CSV data, sets target allocations, and generates trade instructions.

Factor Analysis

Alpha Skills - Python - AI skills for quantitative factor research: discover, evaluate, mine, backtest, and monitor factors through any AI coding assistant. Supports A-share, HK, and US markets.
alphalens - Python - Performance analysis of predictive alpha factors.
alphalens-reloaded - Python - Performance analysis of predictive (alpha) stock factors.
Spectre - Python - GPU-accelerated Factors analysis library and Backtester.
quant-lab-alpha - Python - Open-source investment analytics platform bridging academic research and retail finance.
covFactorModel - R - Covariance matrix estimation via factor models.
FactorAnalytics - R - The FactorAnalytics package contains fitting and analysis methods for the three main types of factor models used in conjunction with portfolio construction, optimization and risk management, namely fundamental factor models, time series factor models and statistical factor models.
Expected Returns - R - Solutions for enhancing portfolio diversification and replications of seminal papers with R, most of which are discussed in one of the best investment references of the recent decade, Expected Returns: An Investors Guide to Harvesting Market Rewards by Antti Ilmanen.

Sentiment Analysis & Alternative Data

Asset News Sentiment Analyzer - Python - Sentiment analysis and report generation package for financial assets and securities utilizing GPT models.
Social Stock Sentiment API - Python - REST API analyzing Reddit and X/Twitter for stock mentions and sentiment, providing buzz scores, trending stocks, and AI-generated trend explanations.
CoWorker Fin-Agent - Python - LLM-powered A-share stock analysis via P2P agent collaboration. Technical analysis (MA60, volume-price patterns, golden eye), deep research reports using proprietary methodology, and market state summaries. Analysis logic stays private via Skill-as-API protocol.
StockKit - TypeScript - Free AI-powered stock research reports for US, China & HK using Claude Opus and multi-model AI with 20+ technical indicators. GitHub

Time Series Analysis

ARCH - Python - ARCH models in Python.
statsmodels - Python - Python module that allows users to explore data, estimate statistical models, and perform statistical tests. GitHub
dynts - Python - Python package for timeseries analysis and manipulation.
PyFlux - Python - Python library for timeseries modelling and inference (frequentist and Bayesian) on models.
tsfresh - Python - Automatic extraction of relevant features from time series.
Facebook Prophet - Python - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
tsmoothie - Python - A python library for time-series smoothing and outlier detection in a vectorized way.
pmdarima - Python - A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
gluon-ts - Python - vProbabilistic time series modeling in Python.
OmniOracle - Python - Automatic discovery of non-trivial statistical relationships across 500+ time series from FRED, World Bank, EIA, and NOAA using mutual information screening, lagged MI directional testing, and FDR correction.
functime - Python - Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
tseries - R - Time Series Analysis and Computational Finance.
fGarch - R - Rmetrics - Autoregressive Conditional Heteroskedastic Modelling.
timeSeries - R - Rmetrics - Financial Time Series Objects.
rugarch - R - Univariate GARCH Models.
rmgarch - R - Multivariate GARCH Models.
tidypredict - R - Run predictions inside the database https://tidypredict.netlify.com/.
tidyquant - R - Bringing financial analysis to the tidyverse.
timetk - R - A toolkit for working with time series in R.
tibbletime - R - Built on top of the tidyverse, tibbletime is an extension that allows for the creation of time aware tibbles through the setting of a time index.
matrixprofile - R - Time series data mining library built on top of the novel Matrix Profile data structure and algorithms.
garchmodels - R - A parsnip backend for GARCH models.
TimeSeries.jl - Julia - Time series toolkit for Julia.
TimeFrames.jl - Julia - A Julia library that defines TimeFrame (essentially for resampling TimeSeries).

Market Data & Data Sources

BTC Orderbook Microstructure Research - Jupyter Notebook - statistical analysis of Binance BTC/USDT orderbook: OBI, CVD, spread.
OpenBB Terminal - Python - Terminal for investment research for everyone.
Fincept Terminal - Python - Advance Data Based A.I Terminal for all Types of Financial Asset Research.
yfinance - Python - Yahoo! Finance market data downloader (+faster Pandas Datareader).
coinpaprika-api-python-client - Python - Free crypto market data API client. 12,000+ coins, 350+ exchanges, tickers, OHLCV, historical prices. No API key for free tier.
defeatbeta-api - Python - An open-source alternative to Yahoo Finance's market data APIs with higher reliability.
financekit-mcp - Python - MCP server (Model Context Protocol) exposing 17 tools for AI agents to perform quantitative analysis: real-time stock quotes, full technical analysis (RSI, MACD, Bollinger, ADX, Stochastic, ATR, OBV + pattern detection with structured verdicts), crypto prices via CoinGecko, risk metrics (VaR, Sharpe, Sortino, Beta, Max Drawdown), correlation matrix, options chains, earnings calendar, sector rotation, and portfolio analysis. Works with Claude Desktop, Cursor, Windsurf. No API keys for core tools. FastMCP 3.2.
dexpaprika-sdk-python - Python - Free DEX data API client. 34 blockchains, 30M+ pools, 27M+ tokens, real-time SSE streaming, OHLCV. No API key needed.
Helium MCP - Python - Live stock/ETF/crypto data with AI-generated bull/bear cases and price forecasts, proprietary ML options pricing with probability ITM and fair value, and news bias scoring across 5,000+ sources. Available as MCP server or API. Free tier: 50 queries, no signup. GitHub
findatapy - Python - Python library to download market data via Bloomberg, Quandl, Yahoo etc.
googlefinance - Python - Python module to get real-time stock data from Google Finance API.
Horus Flow - Python - Sub-second L2 orderflow intelligence MCP server for institutional-grade market microstructure analysis.
yahoo-finance - Python - Python module to get stock data from Yahoo! Finance.
pandas-datareader - Python - Python module to get data from various sources (Google Finance, Yahoo Finance, FRED, OECD, Fama/French, World Bank, Eurostat...) into Pandas datastructures such as DataFrame, Panel with a caching mechanism.
pandas-finance - Python - High level API for access to and analysis of financial data.
pyhoofinance - Python - Rapidly queries Yahoo Finance for multiple tickers and returns typed data for analysis.
yfinanceapi - Python - Finance API for Python.
yql-finance - Python - yql-finance is simple and fast. API returns stock closing prices for current period of time and current stock ticker (i.e. APPL, GOOGL).
ystockquote - Python - Retrieve stock quote data from Yahoo Finance.
jugaad-data - Python - Download historical and live stock data from NSE (National Stock Exchange of India), BSE, and RBI.
nsetools - Python - Python library for extracting real-time data from National Stock Exchange (India).
bsedata - Python - Python library for extracting real-time data from Bombay Stock Exchange (India).
nse-insights-api - Python - Unofficial NSE India API for stock quotes, indices, historical data and more.
wallstreet - Python - Real time stock and option data.
stock_extractor - Python - General Purpose Stock Extractors from Online Resources.
Stockex - Python - Python wrapper for Yahoo! Finance API.
SwapAPI - Python - Free DEX aggregator API returning executable swap calldata across 46 EVM chains. No API key required. GitHub
finsymbols - Python - Obtains stock symbols and relating information for SP500, AMEX, NYSE, and NASDAQ.
FRB - Python - Python Client for FRED® API.
inquisitor - Python - Python Interface to Econdb.com API.
yfi - Python - Yahoo! YQL library.
chinesestockapi - Python - Python API to get Chinese stock price. (Last updated: 2015-03-21).
exchange - Python - Get current exchange rate.
unirate-api - Python - Client for UniRateAPI providing real-time and historical exchange rates for 170+ fiat and crypto currencies plus VAT rates, with a free tier and no credit card required.
Chart Library - Python - Historical chart pattern similarity search API. 24M+ pre-computed embeddings across 15K+ symbols and 10 years of data using pgvector. Returns forward returns, regime analysis, and pattern detection. Also available as MCP server. Website
ticks - Python - Simple command line tool to get stock ticker data.
pybbg - Python - Python interface to Bloomberg COM APIs.
ccy - Python - Python module for currencies.
tushare - Python - A utility for crawling historical and Real-time Quotes data of China stocks. (Last updated: 2024-08-27).
edinetdb - Python - Free API and MCP server for Japanese company financials. Normalizes EDINET XBRL across JP-GAAP, IFRS, and US-GAAP for 3,800+ listed companies with 90 metrics, screening, and securities report text.
edinet-mcp - Python - Parse Japanese XBRL financial statements from EDINET with 161 normalized labels, 26 financial metrics, and multi-company screening.
estat-mcp - Python - Access Japanese government statistics (e-Stat) covering population, GDP, CPI, labor, and trade data with MCP integration and Polars export.
tdnet-disclosure-mcp - Python - Access Japanese timely disclosures (TDNet) via MCP. Retrieve earnings, dividends, forecasts, buybacks, and other filings for 4,000+ listed companies. No API key required.
cn_stock_src - Python - Utility for retrieving basic China stock data from different sources.
coinmarketcap - Python - Python API for coinmarketcap.
coinpulse - Python - Python SDK for cryptocurrency portfolio tracking with real-time prices, P/L calculations, and price alerts. Free tier available.
after-hours - Python - Obtain pre market and after hours stock prices for a given symbol.
bronto-python - Python - Bronto API Integration for Python. GitHub
pytdx - Python - Python Interface for retrieving chinese stock realtime quote data from TongDaXin Nodes.
pdblp - Python - A simple interface to integrate pandas and the Bloomberg Open API.
tiingo - Python - Python interface for daily composite prices/OHLC/Volume + Real-time News Feeds, powered by the Tiingo Data Platform.
iexfinance - Python - Python Interface for retrieving real-time and historical prices and equities data from The Investor's Exchange.
pyEX - Python - Python interface to IEX with emphasis on pandas, support for streaming data, premium data, points data (economic, rates, commodities), and technical indicators.
alpaca-trade-api - Python - Python interface for retrieving real-time and historical prices from Alpaca API as well as trade execution.
metatrader5 - Python - API Connector to MetaTrader 5 Terminal. (Last updated: 2026-02-20).
akshare - Python - AkShare is an elegant and simple financial data interface library for Python, built for human beings! https://akshare.readthedocs.io.
yahooquery - Python - Python interface for retrieving data through unofficial Yahoo Finance API.
investpy - Python - Financial Data Extraction from Investing.com with Python! https://investpy.readthedocs.io/.
yliveticker - Python - Live stream of market data from Yahoo Finance websocket.
bbgbridge - Python - Easy to use Bloomberg Desktop API wrapper for Python.
polygon.io - Python - A python library for Polygon.io financial data APIs.
alpha_vantage - Python - A python wrapper for Alpha Vantage API for financial data.
oilpriceapi - Python - Python SDK for real-time oil and commodity prices (WTI, Brent, Urals, natural gas, coal) with OpenBB integration.
FinanceDataReader - Python - Open Source Financial data reader for U.S, Korean, Japanese, Chinese, Vietnamese Stocks.
pystlouisfed - Python - Python client for Federal Reserve Bank of St. Louis API - FRED, ALFRED, GeoFRED and FRASER.
python-bcb - Python - Python interface to Brazilian Central Bank web services.
swiss-finance-data - Python - Python package for Swiss financial data (SNB Policy Rate, SARON, CHF FX rates, CPI, SMI equities, Confederation bond yields) from official SNB sources.
market-prices - Python - Create meaningful OHLCV datasets from knowledge of exchange-calendars (works out-the-box with data from Yahoo Finance).
tardis-python - Python - Python interface for Tardis.dev high frequency crypto market data.
lake-api - Python - Python interface for Crypto Lake high frequency crypto market data.
tessa - Python - simple, hassle-free access to price information of financial assets (currently based on yfinance and pycoingecko), including search and a symbol class.
pandaSDMX - Python - Python package that implements SDMX 2.1 (ISO 17369:2013), a format for exchange of statistical data and metadata used by national statistical agencies, central banks, and international organisations.
cif - Python - Python package that include few composite indicators, which summarize multidimensional relationships between individual economic indicators.
finagg - Python - finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML.
FinanceDatabase - Python - This is a database of 300.000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies and Money Markets.
Trading Strategy - Python - download price data for decentralised exchanges and lending protocols (DeFi).
datamule-python - Python - A package to work with SEC data. Incorporates datamule endpoints.
fsynth - Python - Python library for high-fidelity unlimited synthetic financial data generation using Heston Stochastic Volatility and Merton Jump Diffusion.
fedfred - Python - FRED & GeoFRED Economic data API with preprocessed dataframe output in pandas/geopandas, polars/polars_st, and dask dataframes/geodataframes.
edgar-sec - Python - EDGAR Financial data API with preprocessed dataclass outputs.
edgartools - Python - AI-native SEC EDGAR library with XBRL financials, clean text extraction, 17+ typed forms, and pandas DataFrames.
FXMacroData - Python - Real-time forex macroeconomic API for all major currency pairs sourced from central bank announcements. GitHub
uk-sic-codes - Python - UK SIC 2007 industry classification code lookup, search, and validation. 731 codes, 21 sections. PyPI
uk-company-number - Python - Validate, format, and identify UK Companies House company numbers. Supports all 27 prefixes. PyPI
veroq-python - Python - Financial intelligence API with verified market data, trading signals, sentiment analysis, and fact-checking across 1,061+ tickers. PyPI
IBrokers - R - Provides native R access to Interactive Brokers Trader Workstation API.
Rblpapi - R - An R Interface to 'Bloomberg' is provided via the 'Blp API'.
Rbitcoin - R - Unified markets API interface (bitstamp, kraken, btce, bitmarket).
GetTDData - R - Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto.
GetHFData - R - Downloads and aggregates high frequency trading data for Brazilian instruments directly from Bovespa ftp site.
td - R - Interfaces the 'twelvedata' API for stocks and (digital and standard) currencies.
rbcb - R - R interface to Brazilian Central Bank web services.
rb3 - R - A bunch of downloaders and parsers for data delivered from B3.
simfinapi - R - Makes 'SimFin' data (https://simfin.com/) easily accessible in R.
tidyfinance - R - Tidy Finance helper functions to download financial data and process the raw data into a structured Format (tidy data), including.
CcyConv.jl - Julia - Currency conversion library for Julia.
CryptoExchangeAPIs.jl - Julia - A Julia library for cryptocurrency exchange APIs.
MarketData.jl - Julia - Time series market data.
OnlineResamplers.jl - Julia - High-performance Julia package for real-time resampling of financial market data.
PENDAX - JavaScript - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More.
PreReason - JavaScript - Pre-analyzed Bitcoin and macro market briefings for AI agents. 17 contexts with trend signals, confidence scores, and regime classification via REST API and MCP.
marketstore - Golang - DataFrame Server for Financial Timeseries Data.
fin-stream - Rust - Real-time market data streaming in Rust: lock-free SPSC ring buffer, 100K+ ticks/second ingestion, multi-timeframe OHLCV construction, and Lorentz transforms on financial time series.
finalytics - Rust - A rust library for financial data analysis.
Coinugget - Web - Real-time RSI signals, price action & volume spikes dashboard across multiple exchanges. Free, no sign-up required.

Prediction Markets

pmxt - Python JavaScript - The CCXT for prediction markets. A unified API for trading on Polymarket, Kalshi, and more.
polymarket-whales - Python - Real-time whale trade tracker for Polymarket — terminal alerts + Telegram notifications when large orders hit the book.
Polymarket Scanner API - Python - Real-time arbitrage detection API for Polymarket prediction markets, scanning 12,000+ markets for mispricings.
SimpleFunctions - JavaScript - Prediction market intelligence CLI for Kalshi and Polymarket. Causal thesis models, edge detection, 24/7 orderbook monitoring, what-if scenarios, and trade execution. MCP server for AI agent integration.
pmxt - Python JavaScript - The CCXT for prediction markets. A unified API for trading on Polymarket, Kalshi, and more.
PolyMind - Python - Real-time Polymarket trading alerts with multi-AI analysis (Groq, Claude, Gemini). Track whale bets, volume spikes, coordinated wallets, and 12 signal types. Free tier available. GitHub
prediction-market-maker - Python - Open-source market-making strategy that placed #2 in Paradigm's prediction market challenge, with full strategy evolution and analysis.

Calendars & Market Hours

exchange_calendars - Python - Stock Exchange Trading Calendars.
bizdays - Python - Business days calculations and utilities.
pandas_market_calendars - Python - Exchange calendars to use with pandas for trading applications.
timeDate - R - Chronological and Calendar Objects.
bizdays - R - Business days calculations and utilities.

Visualization

D-Tale - Python - Visualizer for pandas dataframes and xarray datasets.
mplfinance - Python - matplotlib utilities for the visualization, and visual analysis, of financial data.
finplot - Python - Performant and effortless finance plotting for Python.
finvizfinance - Python - Finviz analysis python library.
market-analy - Python - Analysis and interactive charting using market-prices and bqplot.
QuantInvestStrats - Python - Quantitative Investment Strategies (QIS) package implements Python analytics for visualisation of financial data, performance reporting, analysis of quantitative strategies.
LightweightCharts.jl - Julia - Julia wrapper for Lightweight Charts™ by TradingView.
QUANTAXIS_Webkit - JavaScript - An awesome visualization center based on quantaxis.

Excel & Spreadsheet Integration

xlwings - Python - Make Excel fly with Python. GitHub
openpyxl - Python - Read/Write Excel 2007 xlsx/xlsm files.
xlrd - Python - Library for developers to extract data from Microsoft Excel spreadsheet files.
xlsxwriter - Python - Write files in the Excel 2007+ XLSX file format. GitHub
xlwt - Python - Library to create spreadsheet files compatible with MS Excel 97/2000/XP/2003 XLS files, on any platform.
xlloop - Python - XLLoop is an open source framework for implementing Excel user-defined functions (UDFs) on a centralised server (a function server). GitHub
expy - Python - The ExPy add-in allows easy use of Python directly from within an Microsoft Excel spreadsheet, both to execute arbitrary code and to define new Excel functions.
pyxll - Python - PyXLL is an Excel add-in that enables you to extend Excel using nothing but Python code.

Quant Research Environments

Jupyter Quant - Python - A dockerized Jupyter quant research environment with preloaded tools for quant analysis, statsmodels, pymc, arch, py_vollib, zipline-reloaded, PyPortfolioOpt, etc.

Cross-Language Frameworks

RunMat - High performance, Open Source, MATLAB syntax runtime. GitHub
QuantLib - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
QuantLibRisks - Fast risks with QuantLib in C++.
XAD - Automatic Differentation (AAD) Library.
QuantLib - The QuantLib project is aimed at providing a comprehensive software framework for quantitative finance.
- QuantLibRisks - Fast risks with QuantLib in Python and C++
- XAD - Automatic Differentiation (AAD) Library in Python and C++
- JQuantLib - Java port.
- RQuantLib - R port.
- QuantLibAddin - Excel support.
- QuantLibXL - Excel support.
- QLNet - .Net port.
- PyQL - Python port.
- QuantLib.jl - Julia port.
- QuantLib-Python Documentation - Documentation for the Python bindings for the QuantLib library.
TA-Lib - perform technical analysis of financial market data. GitHub
- ta-lib-python
- ta-lib
RunMat - Rust runtime for MATLAB-syntax array math with automatic CPU/GPU execution and fused kernels for quant simulations.

Reproducing Works, Training & Books

Special-Relativity-in-Financial-Modeling - C++20 implementation of special-relativistic geometry applied to OHLCV data: Lorentz factors, spacetime intervals, Christoffel symbols, and geodesic deviation signals from live market data. DOI: 10.5281/zenodo.18639919.
Auto-Differentiation Website - Background and resources on Automatic Differentiation (AD) / Adjoint Algorithmic Differentitation (AAD).
Derman Papers - Notebooks that replicate original quantitative finance papers from Emanuel Derman.
volatility-trading - A complete set of volatility estimators based on Euan Sinclair's Volatility Trading.
quant - Quantitative Finance and Algorithmic Trading exhaust; mostly ipython notebooks based on Quantopian, Zipline, or Pandas.
fecon235 - Open source project for software tools in financial economics. Many jupyter notebook to verify theoretical ideas and practical methods interactively.
Quantitative-Notebooks - Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy.
QuantEcon - Lecture series on economics, finance, econometrics and data science; QuantEcon.py, QuantEcon.jl, notebooks.
FinanceHub - Resources for Quantitative Finance.
Python_Option_Pricing - An library to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options.
python-training - J.P. Morgan's Python training for business analysts and traders.
Stock_Analysis_For_Quant - Different Types of Stock Analysis in Excel, Matlab, Power BI, Python, R, and Tableau.
algorithmic-trading-with-python - Source code for Algorithmic Trading with Python (2020) by Chris Conlan.
MEDIUM_NoteBook - Repository containing notebooks of cerlymarco's posts on Medium.
QuantFinance - Training materials in quantitative finance.
IPythonScripts - Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning.
Computational-Finance-Course - Materials for the course of Computational Finance.
Machine-Learning-for-Asset-Managers - Implementation of code snippets, exercises and application to live data from Machine Learning for Asset Managers (Elements in Quantitative Finance) written by Prof. Marcos López de Prado.
Python-for-Finance-Cookbook - Python for Finance Cookbook, published by Packt.
modelos_vol_derivativos - "Modelos de Volatilidade para Derivativos" book's Jupyter notebooks.
NMOF - Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658).
py4fi2nd - Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.
aiif - Jupyter Notebooks and code for the book Artificial Intelligence in Finance (O'Reilly) by Yves Hilpisch.
py4at - Jupyter Notebooks and code for the book Python for Algorithmic Trading (O'Reilly) by Yves Hilpisch.
dawp - Jupyter Notebooks and code for Derivatives Analytics with Python (Wiley Finance) by Yves Hilpisch.
dx - DX Analytics | Financial and Derivatives Analytics with Python.
QuantFinanceBook - Quantitative Finance book.
rough_bergomi - A Python implementation of the rough Bergomi model.
frh-fx - A python implementation of the fast-reversion Heston model of Mechkov for FX purposes.
Value Investing Studies - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.
Machine Learning Asset Management - Machine Learning in Asset Management (by @firmai).
Deep Learning Machine Learning Stock - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.
Technical Analysis and Feature Engineering - Feature Engineering and Feature Importance of Machine Learning in Financial Market.
Differential Machine Learning and Axes that matter by Brian Huge and Antoine Savine - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.
systematictradingexamples - Examples of code related to book Systematic Trading and blog.
pysystemtrade_examples - Examples using pysystemtrade for Robert Carver's blog.
ML_Finance_Codes - Machine Learning in Finance: From Theory to Practice Book.
cipher-starter — Solo crypto quant starter kit: 12 playbooks covering trading strategy, risk rails, 3-tier wallet architecture, MEV mitigation, Canadian NI 31-103 compliance, Oracle Cloud Always Free infra, and a 7-day MVP calendar for a Solana signal engine + autonomous trading bot.
Hands-On Machine Learning for Algorithmic Trading - Hands-On Machine Learning for Algorithmic Trading, published by Packt.
financialnoob-misc - Codes from @financialnoob's posts.
MesoSim Options Trading Strategy Library - Free and public Options Trading strategy library for MesoSim.
Quant-Finance-With-Python-Code - Repo for code examples in Quantitative Finance with Python by Chris Kelliher.
QuantFinanceTraining - This repository contains codes that were executed during my training in the CQF (Certificate in Quantitative Finance). The codes are organized by class, facilitating navigation and reference.
Statistical-Learning-based-Portfolio-Optimization - This R Shiny App utilizes the Hierarchical Equal Risk Contribution (HERC) approach, a modern portfolio optimization method developed by Raffinot (2018).
book_irds3 - Code repository for Pricing and Trading Interest Rate Derivatives.
Autoencoder-Asset-Pricing-Models - Reimplementation of Autoencoder Asset Pricing Models (GKX, 2019).
Finance - 150+ quantitative finance Python programs to help you gather, manipulate, and analyze stock market data.
101_formulaic_alphas - Implementation of 101 formulaic alphas using qstrader.
Tidy Finance - An opinionated approach to empirical research in financial economics - a fully transparent, open-source code base in multiple programming languages (Python and R) to enable the reproducible implementation of financial research projects for students and practitioners.
RoughVolatilityWorkshop - 2024 QuantMind's Rough Volatility Workshop lectures.
AFML - All the answers for exercises from Advances in Financial Machine Learning by Dr Marco Lopez de Parodo.
AlgoTradingLib - A catalog of algorithmic trading libraries, frameworks, strategies, and educational materials.
Portfolio Optimization Book - Prof. Daniel Palomar's Portfolio Optimization Book. GitHub

Commercial & Proprietary Services

Chartscout - Real-time cryptocurrency chart pattern detection with automated alerts across multiple exchanges.
DayTradingBench - Live autonomous benchmark that evaluates LLM trading performance on DAX and Nasdaq indices using identical strategies and real-time market data. API access available.
CoinTester - No-code crypto backtesting platform with 100+ indicators, AI sentiment signals, and 5+ years of historical data across 1,000+ trading pairs.
goMacro.ai - AI-powered economic calendar with institutional-grade insights, bull/bear/base case scenario planning for NFP, CPI, PPI and other macro data releases.
StockAInsights - AI-extracted financial statements API covering SEC filings including foreign filers (20-F, 6-K, 40-F), normalized quarterly and annual data from 2014+.
bolsai - REST API and MCP server for Brazilian stock market data (B3). Covers 350+ stocks, 400+ FIIs with fundamentals (27+ indicators), dividends, historical prices, financials, and macro indicators sourced from B3, CVM, and BCB.
brapi.dev - Brazilian stock market data API for B3/Bovespa quotes, historical OHLCV, dividends, and fundamentals.
13F Insight - Track institutional investor 13F holdings with AI-powered analysis, position change alerts, and filing summaries.
Earnings Feed - Real-time SEC filings, insider trades, and institutional holdings API.
Financial Data - Stock Market and Financial Data API.
Frostbyte - Real-time crypto prices for 500+ tokens via REST API with free tier, DeFi swap routing and portfolio tracking.
SaxoOpenAPI - Saxo Bank financial data API.
RTPR - Real-time press release API delivering news from Business Wire, PR Newswire, and GlobeNewswire with sub-500ms latency. REST and WebSocket APIs for financial applications. Python and Node.js SDKs available.
Nasdaq Data Link - Financial data API with support for R, Python, Excel, Ruby, and many other languages (formerly Quandl).
Parsec - Prediction market API with Python SDK for normalized data and execution across 5 prediction market exchanges. Free tier: 10K requests/month.
Portfolio Optimizer - Portfolio Optimizer is a Web API for portfolio analysis and optimization.
Reddit WallstreetBets API - Provides daily top 50 stocks from reddit (subreddit) Wallstreetbets and their sentiments via the API.
System R - AI-native risk intelligence API for trading agents. Position sizing, risk validation, and system health in one call.
Telonex - Tick-level prediction market data (trades, quotes, orderbooks, on-chain fills) via REST API and Python SDK.
ValueRay - Technical, quantitative and sentiment data for stocks and ETFs with risk metrics, peer percentiles and market regime signals. Optimized for AI/LLM agents.
VertData - Institutional-grade financial intelligence platform. Track 43K+ congressional trades (STOCK Act), SEC insider Form 4 filings, 25 superinvestor 13F portfolios, CFTC futures positioning, ARK ETF holdings, and short interest — all scored by AI for signal strength.
KeepRule - Curated library of decision-making principles and investment wisdom from masters like Buffett and Munger, featuring mental models for better investment thinking.
ML-Quant - Top Quant resources like ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.
RealMarketAPI - Provides ultra-low latency market data for gold, forex, crypto, and stocks via REST, WebSocket, and MCP—built for speed, reliability, and scale.
Webb Database - Aggregates public financial data from HKEX, the SFC, the Hong Law Society, UK Companies House and other sources, has searchable datasets on listed companies, many in machine-readable formats.
GitDealFlow - Alternative-data signal platform ranking early-stage private companies by GitHub stars-per-day, hiring velocity, and package-registry adoption. Free weekly signal report, Chrome extension overlay on Crunchbase/AngelList, and MCP server on npm for LLM agent access.

Related Lists

awesome-sec-filings - A curated list of tools, data sources, libraries, and resources for working with SEC filings (13F, 10-K, 10-Q, 8-K).
CONVEXFI - Official GitHub organization for the convex research group at the Hong Kong University of Science and Technology (HKUST).

tractorjuice/arc-kit

Enterprise Architecture Governance & Vendor Procurement Toolkit

ArcKit - Enterprise Architecture Governance Toolkit

Build better enterprise architecture through structured governance, vendor procurement, and design review workflows.

ArcKit is a toolkit for enterprise architects that transforms architecture governance from scattered documents into a systematic, AI-assisted workflow for:

🏛️ Establishing and enforcing architecture principles
👥 Analyzing stakeholder drivers, goals, and outcomes
🛡️ Risk management (HM Treasury Orange Book)
💼 Business case justification (HM Treasury Green Book SOBC)
📋 Creating comprehensive requirements documents
🗄️ Data modeling with ERD, GDPR compliance, and data governance
🔬 Technology research with build vs buy analysis (web search powered)
☁️ Azure-specific research using Microsoft Learn MCP for authoritative documentation
🗺️ Strategic planning with Wardley Mapping
📊 Generating visual architecture diagrams (Mermaid)
🤝 Managing vendor RFP and selection processes
✅ Conducting formal design reviews (HLD/DLD)
🔧 ServiceNow service management design
🔗 Maintaining requirements traceability
📎 Citation traceability for external documents (inline [DOC-CN] markers with source quotes)

📖 The ArcKit Book

A comprehensive book-length guide to ArcKit — covering every subsystem (commands, agents, hooks, skills, MCP servers, multi-AI distribution, templates, autoresearch) — now lives in its own repository: tractorjuice/arckit-book.

Star History

Quick Start

Installation

Claude Code (premier experience) — install the ArcKit plugin (requires v2.1.129+):

First, make sure Claude Code is on the latest version:

claude install latest

Then in Claude Code:

/plugin marketplace add tractorjuice/arc-kit

Then install from the Discover tab.

Tip: lighter marketplace clone. The command above clones the full arc-kit monorepo (~100 MB) because it hosts five other AI-assistant distributions, 147 vendored Wardley maps, and research docs you don't need. To fetch just the plugin's directories, add the marketplace via the CLI with --sparse:
claude plugin marketplace add tractorjuice/arc-kit --sparse .claude-plugin arckit-claude
This uses git sparse-checkout to limit the clone to .claude-plugin/ (the marketplace catalog) and arckit-claude/ (the plugin itself). Works with Claude Code's documented marketplace sparse flag. Claude Code is the primary development platform for ArcKit and provides the most complete experience: all 70 official commands (plus 46 community-contributed), 10 autonomous research agents, 5 automation hooks (session init, project context injection, filename enforcement, output validation, impact scan), bundled MCP servers (AWS Knowledge, Microsoft Learn, Google Developer Knowledge, govreposcrape), and automatic updates via the marketplace. See Why Claude Code? below.

Why v2.1.129? Claude Code v2.1.129 moved the plugin manifest's monitors (and themes) keys under a top-level experimental block — ArcKit's stale-artifact-scan background monitor (which warns when projects/ artefacts are past their Next Review Date or stuck in DRAFT for 14+ days) is declared via that key and will not load on older clients. The same release also fixed a regression that was silently downgrading the ENABLE_PROMPT_CACHING_1H 1-hour prompt cache TTL back to 5 minutes — the autoresearch + multi-command workflow guidance documented in this repo only delivers the promised 1h TTL on v2.1.129+. Carries forward the v2.1.121 unlocks: MCP alwaysLoad eager-loads AWS Knowledge and Microsoft Learn tools at session start (skips a discovery round-trip on /arckit:aws-research and /arckit:azure-research), and PostToolUse hookSpecificOutput.updatedToolOutput so provenance-stamp and manifest hooks surface their effects to the model in-band; the v2.1.118–119 release-flow unlocks: claude plugin tag --dry-run validates plugin/marketplace version agreement, and the session-telemetry hook records duration_ms on every tool call; the v2.1.117 unlocks: Opus 4.7 /context correctly sized to 1M instead of 200K (long research sessions no longer autocompact early) and agent frontmatter mcpServers loading for --agent sessions; the v2.1.111+ unlocks: Opus 4.7 xhigh effort tier, Auto mode without --enable-auto-mode, read-only bash glob patterns without permission prompts; and the v2.1.97 fixes: claude plugin update correctly detects new commits for git-based plugins (critical for ArcKit distribution), MCP HTTP/SSE memory leak fix (~50 MB/hr, affects ArcKit's 5 bundled servers), proper 429 exponential backoff (benefits 10 research agents), Stop/SubagentStop hooks no longer fail on long sessions (affects session-learner), and subagent working directory leak fix.

Gemini CLI — install the ArcKit extension:

gemini extensions install https://github.com/tractorjuice/arckit-gemini

Zero-config: all 70 official commands (plus 46 community-contributed overlays), templates, scripts, and bundled MCP servers (AWS Knowledge, Microsoft Learn). Updates via gemini extensions update arckit.

GitHub Copilot (VS Code) — install the ArcKit CLI and scaffold prompt files:

# Install with pip
pip install git+https://github.com/tractorjuice/arc-kit.git

# Scaffold a project with Copilot prompt files
arckit init my-project --ai copilot

Creates .github/prompts/arckit-*.prompt.md (80 prompt files), .github/agents/arckit-*.agent.md (10 custom agents), and .github/copilot-instructions.md (repo-wide context). Invoke commands in Copilot Chat as /arckit-requirements, /arckit-stakeholders, etc.

Codex CLI — install the ArcKit CLI:

# Install with pip
pip install git+https://github.com/tractorjuice/arc-kit.git

# Or with uv
uv tool install arckit-cli --from git+https://github.com/tractorjuice/arc-kit.git

# Or run without installing
uvx --from git+https://github.com/tractorjuice/arc-kit.git arckit init my-project

Latest Release: v4.20.3

Platform Support

Platform	Claude Code Plugin	Gemini CLI Extension	GitHub Copilot	Codex / OpenCode CLI
macOS	Full support	Full support	Full support	Full support
Linux	Full support	Full support	Full support	Full support
Windows (WSL2)	Full support	Full support	Full support	Full support
Windows (native)	Full support	Full support	Full support	Partial

Windows users: The Claude Code plugin, Gemini CLI extension, and GitHub Copilot prompt files work natively on all platforms. For Codex CLI / OpenCode CLI on native Windows (without WSL), some commands containing inline bash snippets may require Git Bash or WSL2. We recommend WSL2 for the best experience.

Initialize a Project

Claude Code: No initialization needed — the plugin provides everything.

GitHub Copilot (VS Code):

# Create a new architecture governance project
arckit init payment-modernization --ai copilot

# Or initialize in current directory
arckit init . --ai copilot

OpenCode CLI:

# Create a new architecture governance project
arckit init payment-modernization --ai opencode

# Or initialize in current directory
arckit init . --ai opencode

Codex CLI:

# Create a new architecture governance project
arckit init payment-modernization --ai codex

# Minimal install (skip docs and guides)
arckit init payment-modernization --ai codex --minimal

# Or initialize in current directory
arckit init . --ai codex

Start Using ArcKit

# GitHub Copilot (VS Code)
cd payment-modernization && code .
# In Copilot Chat, use ArcKit commands:
/arckit-principles Create principles for a financial services company
/arckit-requirements Build a payment processing system...

# Codex CLI
cd payment-modernization
codex
# Inside your AI assistant, use ArcKit commands:
/arckit.principles Create principles for a financial services company
/arckit.requirements Build a payment processing system...
/arckit.sow Generate RFP for vendor selection

Upgrading

Claude Code plugin: Updates are automatic via the marketplace — no action needed.

Gemini CLI extension: Updates via gemini extensions update arckit.

GitHub Copilot: Re-run arckit init --here --ai copilot to update prompt files, agents, and instructions.

Codex CLI:

# Step 1: Upgrade the CLI tool
pip install --upgrade git+https://github.com/tractorjuice/arc-kit.git
# Or with uv:
uv tool upgrade arckit-cli --from git+https://github.com/tractorjuice/arc-kit.git

# Step 2: Update your existing project (re-run init in place)
cd /path/to/your-existing-project
arckit init --here --ai codex

This updates commands, templates, scripts, and agents while preserving your project data (projects/) and custom templates (.arckit/templates-custom/).

If upgrading from v0.x, you may also need to migrate legacy filenames — see the upgrading guide for full details.

Explore Example Outputs

Public demonstration repositories showcase complete ArcKit deliverables:

NHS Appointment Booking — arckit-test-project-v7-nhs-appointment: Digital health platform with NHS Spine integration and GDPR safeguards.
M365 GCC-H Migration — arckit-test-project-v1-m365: Government cloud migration with compliance mapping and change management.
HMRC Tax Assistant — arckit-test-project-v2-hmrc-chatbot: Conversational AI service covering PII protection and bilingual support.
Windows 11 Deployment — arckit-test-project-v3-windows11: Enterprise OS rollout with policy migration and security baselines.
Patent Application System — arckit-test-project-v6-patent-system: Intellectual property workflow automation using GOV.UK Pay and Notify.
ONS Data Platform — arckit-test-project-v8-ons-data-platform: Official statistics analytics environment with Five Safes governance.
Cabinet Office GenAI Platform — arckit-test-project-v9-cabinet-office-genai: Cross-government GenAI platform with responsible AI guardrails.
UK Government Training Marketplace — arckit-test-project-v10-training-marketplace: AI training procurement platform with multi-sided marketplace design.
National Highways Data Architecture — arckit-test-project-v11-national-highways-data: Strategic road network data platform modernization.
Scottish Courts GenAI — arckit-test-project-v14-scottish-courts: Scottish Courts and Tribunals Service GenAI strategy with comprehensive MLOps and FinOps.
Doctors Appointment System — arckit-test-project-v16-doctors-appointment: Online appointment booking system with NHS integration.
UK Fuel Price Transparency — arckit-test-project-v17-fuel-prices: UK Government fuel price transparency service with real-time pricing data.
Smart Meter Consumer App — arckit-test-project-v18-smart-meter: UK Smart Meter data consumer mobile app with DCC/SMIP integration.
UK Government API Aggregator — arckit-test-project-v19-gov-api-aggregator: Unified access to 240+ UK Government APIs across 34+ departments.

Why ArcKit?

Problem: Architecture Governance is Broken

Traditional enterprise architecture suffers from:

❌ Scattered documents across tools (Word, Confluence, PowerPoint)
❌ Inconsistent governance enforcement
❌ Manual vendor evaluation with bias
❌ Lost traceability between requirements and design
❌ Stale documentation that doesn't match reality

Solution: Structured, AI-Assisted Governance

ArcKit provides:

✅ Template-Driven Quality: Comprehensive templates ensure nothing is forgotten
✅ Systematic Workflows: Clear processes from requirements → procurement → design review
✅ AI Assistance: Let AI handle document generation, you focus on decisions
✅ Enforced Traceability: Automatic gap detection and coverage analysis
✅ Version Control: Git-based workflow for all architecture artifacts

UK Government Compliance

ArcKit includes dedicated commands for UK public sector delivery:

/arckit.tcop — Assess all 13 Technology Code of Practice points across delivery phases.
/arckit.ai-playbook — Produce responsible AI assessments aligned to the UK Government AI Playbook and ATRS.
/arckit.secure — Generate Secure by Design artefacts covering NCSC CAF, Cyber Essentials, and UK GDPR controls.
/arckit.mod-secure — Map MOD Secure by Design requirements (JSP 440, IAMM, clearance pathways).
/arckit.jsp-936 — Deliver JSP 936 AI assurance packs for defence AI systems.

See the demo repositories for end-to-end examples, especially arckit-test-project-v7-nhs-appointment (civilian services) and arckit-test-project-v9-cabinet-office-genai (AI governance).

EU, French & Austrian Regulatory Compliance (Community)

⚠️ Community-contributed. EU and French commands are domain-maintained by @thomas-jardinet; Austrian commands are a seed contribution inviting an Austrian domain maintainer. The 21 commands below cover EU regulations (GDPR, NIS2, AI Act, DORA, CRA, DSA, Data Act), French government standards (SecNumCloud, ANSSI, EBIOS, CNIL, DINUM, etc.), and Austrian government standards (DSG, NISG 2024, BVergG 2018). They are not part of the officially-maintained baseline — output should be reviewed by qualified DPO / CISO / Vergabejurist / legal counsel before reliance, and citations may lag current source text. Each command surfaces with a [COMMUNITY] prefix in /help listings and renders a warning banner before generating.

EU regulations (member-state-neutral baselines, applicable across EU/EEA):

/arckit.eu-rgpd — GDPR (EU 2016/679) compliance assessment — legal basis, data subject rights, transfers, DPIA screening, breach notification
/arckit.eu-nis2 — NIS2 Directive — operators of essential / important entities, Article 21 measures, incident reporting timelines
/arckit.eu-ai-act — EU AI Act (Regulation 2024/1689) — risk classification (prohibited / high-risk / GPAI), conformity routes
/arckit.eu-dora — Digital Operational Resilience Act (EU 2022/2554) — financial sector ICT risk, TLPT, third-party register
/arckit.eu-cra — Cyber Resilience Act (Regulation 2024/2847) — products with digital elements, SBOM, VDP, CE marking
/arckit.eu-dsa — Digital Services Act (Regulation 2022/2065) — intermediaries, platforms, VLOPs, ARCOM
/arckit.eu-data-act — Data Act (Regulation 2023/2854) — connected products, B2B FRAND, cloud switching, Article 27

French government (apply on top of the EU baseline for French deployments):

/arckit.fr-secnumcloud — SecNumCloud 3.2 qualification (sovereign cloud, OIV/OSE, extraterritorial risk)
/arckit.fr-dinum — DINUM standards: RGI, RGAA, RGESN, RGS, doctrine cloud de l'État, FranceConnect, DSFR
/arckit.fr-marche-public — French public procurement (code de la commande publique, UGAP, sovereignty clauses)
/arckit.fr-rgpd — CNIL-specific GDPR layer (cookies Délibération 2020-091, HDS, age 15, DPO registration)
/arckit.fr-ebios — EBIOS Risk Manager — 5-workshop study (VM/ER/SR/CO/SS/SO/MS IDs, MITRE ATT&CK, homologation)
/arckit.fr-anssi — ANSSI Guide d'hygiène informatique (42 measures) + cloud security recommendations
/arckit.fr-anssi-carto — ANSSI SI cartography across business / application / system / network levels
/arckit.fr-dr — Diffusion Restreinte handling under II 901 / SGDSN / ANSSI
/arckit.fr-algorithme-public — Public algorithm transparency notice (Article L311-3-1 CRPA, Loi République Numérique)
/arckit.fr-pssi — Information System Security Policy (PSSI) per ANSSI / RGS
/arckit.fr-code-reuse — Public code reuse assessment (code.gouv.fr, SILL, EUPL) — build-vs-reuse decision matrix

Austrian government (apply on top of the EU baseline for Austrian deployments — seed contribution pending a domain maintainer):

/arckit.at-dsgvo — Austrian DSG layer on GDPR (§§12–13 image processing, ELGA/GTelG health, §96a ArbVG employee monitoring, age 14 consent, DSB enforcement)
/arckit.at-nisg — Austrian NISG 2024 (NIS2 transposition) — Essential/Important designation, GovCERT reporting, KSÖ, AT sectoral authorities
/arckit.at-bvergg — Bundesvergabegesetz 2018 procurement — Oberschwellen/Unterschwellen, ANKÖ publication, Bestbieterprinzip, BVwG review

These layer cleanly on the existing baseline — fr-rgpd / at-dsgvo extend eu-rgpd, fr-pssi / at-nisg reference eu-nis2, and fr-secnumcloud integrates with arckit.research and arckit.evaluate for procurement workflows. Austrian commands carry extra [NEEDS VERIFICATION] markers reflecting their seed status — a future domain maintainer is expected to tighten the citations.

Canada Federal Overlay (12 commands)

Federal Canadian regulatory baseline as a [COMMUNITY] overlay — covering FITAA (Bill C-70 2024), federal privacy and access (Privacy Act, ATI Act), Treasury Board Directive on Automated Decision-Making, Charter rights design review, ITSG-33 + Standard on Security Categorization, Security of Information Act handling, GC Cloud sovereign residency, GC Digital Standards conformance, Official Languages Act, federal procurement (PSPC + PSAB), and First Nations OCAP® data sovereignty.

Command	Type code	Purpose
`/arckit:ca-fitaa`	`FITAA`	Foreign Influence Transparency and Accountability Act compliance assessment
`/arckit:ca-pia`	`PIA`	Privacy Impact Assessment per Privacy Act + TBS Directive on PIA
`/arckit:ca-atip`	`ATIP`	Access to Information / Privacy Act reconciliation and severance design
`/arckit:ca-aia`	`AIA`	Algorithmic Impact Assessment per TBS Directive on Automated Decision-Making (Levels I–IV)
`/arckit:ca-charter`	`CHRT`	Charter rights design review (s.2 / s.7 / s.8 / s.15) with Oakes proportionality
`/arckit:ca-itsg-33`	`ITSG`	ITSG-33 Statement of Applicability + Standard on Security Categorization
`/arckit:ca-soia`	`SOIA`	Security of Information Act handling plan for SECRET / TOP SECRET systems
`/arckit:ca-cloud-residency`	`CACR`	GC Cloud sovereign residency assessment with CLOUD-Act analysis
`/arckit:ca-gc-digital-standards`	`DIGSTD`	Government of Canada Digital Standards conformance scorecard
`/arckit:ca-ola`	`OLA`	Official Languages Act review (Parts IV / V / VI)
`/arckit:ca-pspc`	`PROC`	Federal procurement strategy (PSPC Supply Manual + PSAB 5%)
`/arckit:ca-ocap`	`OCAP`	First Nations OCAP® sovereignty assessment with FNIGC pre-engagement gate

Help wanted: looking for a Canadian federal enterprise architect to co-maintain this overlay. Open an issue or DM @tractorjuice.

UAE Federal Overlay (Community-contributed)

⚠️ Community-contributed overlay. The 12 commands below cover UAE federal regulatory and digital-government instruments and ship as a community-contributed overlay (not part of the officially-maintained baseline of 68). They are anchored on the UAE Cabinet decree of 23 April 2026 mandating that 50% of federal services run on agentic AI by April 2028, and on the federal data, identity, AI governance, and procurement frameworks the decree references. The overlay is currently solo-maintained by @tractorjuice; a UAE domain co-maintainer is being recruited before the overlay can be re-evaluated for official-baseline promotion. Six citations are flagged [NEEDS VERIFICATION] pending Executive Regulations and authority confirmations — see docs/guides/uae-overlay-maintenance.md. Output should be reviewed by qualified UAE federal compliance counsel before reliance.

Set governance_framework: UAE Federal and classification_scheme: UAE Smart Data in plugin userConfig to switch the Document Control header into UAE Smart Data classification rendering across every artefact.

Federal data and security:

/arckit.uae-classification — UAE Smart Data Classification Register (Open / Shared / Confidential / Secret / Top Secret) with handling rules and declassification schedule
/arckit.uae-pdpl — Federal Decree-Law No. 45 of 2021 (PDPL) compliance assessment — DPIA, lawful-basis register, data-subject-rights procedure, cross-border transfer log
/arckit.uae-ias — UAE Cybersecurity Council Information Assurance Standard v2 — Statement of Applicability against 188 controls (60 management M1–M6, 128 technical T1–T9), priority-tiered P1–P4
/arckit.uae-cloud-residency — National Cloud Security Policy v2 sovereign cloud assessment — per-classification residency, approved CSPs (Core42 / G42, Microsoft UAE North/Central, TDRA FedNet, e& Sovereign Launchpad on AWS), shared-responsibility matrix, exit/portability plan

Federal identity:

/arckit.uae-uaepass — UAE Pass integration design (OIDC/OAuth flow, claim mapping, Basic vs Verified profile selection, Service Provider onboarding, e-signature audit trail)

Cabinet instruments:

/arckit.uae-zero-bureaucracy — Service Catalogue review under the UAE Code for Government Services and Zero Bureaucracy programme
/arckit.uae-digital-records — Digital Records Plan under the UAE Government Services Digital Records Policy (source-of-truth register per service, retention schedule, official-source designation)
/arckit.uae-data-sharing — Data Sharing Agreement under the UAE Government Services Data Sharing Policy ("collect once, use securely") with PDPL lawful basis per share
/arckit.uae-priorities-alignment — National Priorities Alignment Statement under the UAE Federal Government Guide — reuse-vs-build, capability-reuse register (UAE Pass, FedNet), strategy alignment to NIS 2031 / AI 2031 / We the UAE 2031

AI governance:

/arckit.uae-ai-charter — UAE Charter for the Development and Use of AI compliance assessment (12 principles)
/arckit.uae-ai-autonomy-tier — Three-tier AI autonomy posture (Tier 1 internal-productivity, Tier 2 investor-facing-with-approval, Tier 3 regulated/financial) with per-tier guard-rails, approval gates, audit obligations, tier-promotion criteria

Procurement:

/arckit.uae-procurement — Federal procurement strategy under Federal Decree-Law No. 11 of 2023 — ITT/RFP packs against MoF Digital Procurement Platform templates, In-Country Value (ICV) plan, evaluation report structure, contract register

The commands chain together in a canonical order from principles → uae-classification → uae-pdpl → uae-ias → uae-cloud-residency → uae-uaepass → uae-zero-bureaucracy → uae-digital-records → uae-data-sharing → uae-ai-charter → uae-ai-autonomy-tier → uae-priorities-alignment → uae-procurement → sobc → wardley → framework. The reference implementation is the arckit-test-project-v20-uae-moi-ipad test repo. Full guide: docs/guides/uae-overlay.md.

The ArcKit Workflow

ArcKit guides you through the enterprise architecture lifecycle:

Phase 0: Project Planning

/arckit.plan → Create project plan with timeline, phases, and gates

Visualize your entire project delivery:

GDS Agile Delivery phases (Discovery → Alpha → Beta → Live)
Mermaid Gantt chart with timeline, dependencies, and milestones
Workflow diagram showing gates and decision points
Tailored timeline based on project complexity
Integration of all ArcKit commands into schedule
Gate approval criteria for governance

Phase 1: Establish Governance

/arckit.principles → Create enterprise architecture principles

Define your organisation's architecture standards:

Cloud strategy (AWS/Azure/GCP)
Security frameworks (Zero Trust, compliance)
Technology standards
FinOps and cost governance

Phase 2: Stakeholder Analysis

/arckit.stakeholders → Analyze stakeholder drivers, goals, and outcomes

Do this BEFORE business case to understand who cares about the project and why:

Identify all stakeholders (internal and external)
Document underlying drivers (strategic, operational, financial, compliance, risk, personal)
Map drivers to SMART goals
Map goals to measurable outcomes
Create Stakeholder → Driver → Goal → Outcome traceability
Identify conflicts and synergies
Define engagement and communication strategies

Phase 3: Risk Assessment

/arckit.risk → Create comprehensive risk register (Orange Book)

Do this BEFORE business case to identify and assess risks systematically:

Follow HM Treasury Orange Book 2023 framework
Identify risks across 6 categories (Strategic, Operational, Financial, Compliance, Reputational, Technology)
Assess inherent risk (before controls) and residual risk (after controls)
Apply 4Ts response framework (Tolerate, Treat, Transfer, Terminate)
Link every risk to stakeholder from RACI matrix
Monitor risk appetite compliance
Feed into SOBC Management Case Part E

Phase 4: Business Case Justification

/arckit.sobc → Create Strategic Outline Business Case (SOBC)

Do this BEFORE requirements to justify investment and secure approval:

Use HM Treasury Green Book 5-case model (Strategic, Economic, Commercial, Financial, Management)
Analyze strategic options (Do Nothing, Minimal, Balanced, Comprehensive)
Map benefits to stakeholder goals (complete traceability)
Provide high-level cost estimates (Rough Order of Magnitude)
Economic appraisal (ROI range, payback period)
Procurement and funding strategy
Governance and risk management (uses risk register)
Enable go/no-go decision BEFORE detailed requirements work

Phase 5: Define Requirements

/arckit.requirements → Document comprehensive requirements

Create detailed requirements informed by stakeholder goals (if SOBC approved):

Business requirements with rationale
Functional requirements with acceptance criteria
Non-functional requirements (performance, security, scalability, compliance)
Integration requirements (upstream/downstream systems)
Data requirements (DR-xxx)
Success criteria and KPIs

Phase 5.3: Platform Strategy Design (Optional - for Multi-Sided Platforms)

/arckit.platform-design → Design multi-sided platform strategy using Platform Design Toolkit

Use this phase when designing ecosystem-based platforms (Government as a Platform, marketplaces, data platforms):

Ecosystem Canvas: Map supply side, demand side, supporting entities with relationship diagrams
Entity-Role Portraits: Deep dive into 3-5 key entities (context, pressures, goals, gains)
Motivations Matrix: Identify synergies and conflicts across entities with mitigation strategies
Transactions Board: Design 10-20 transactions with cost reduction analysis (search, information, negotiation, coordination, enforcement)
Learning Engine Canvas: 5+ services that help participants improve (data, feedback loops, network effects)
Platform Experience Canvas: Journey maps with business model and unit economics
MVP Canvas: Liquidity bootstrapping strategy to solve chicken-and-egg problem
Platform Design Canvas: Synthesize all 8 canvases into cohesive platform strategy
UK Government Context: Aligns with Government as a Platform (GaaP), TCoP Point 8 (share/reuse), Digital Marketplace

Use Cases: NHS appointment booking, local authority data marketplaces, training procurement platforms, citizen services portals

Phase 5.5: Data Modeling

/arckit.data-model → Create comprehensive data model with ERD

Create data model based on Data Requirements (DR-xxx):

Visual Entity-Relationship Diagram (ERD) using Mermaid
Detailed entity catalog with attributes, types, validation rules
PII identification and GDPR/DPA 2018 compliance
Data governance matrix (business owners, stewards, custodians)
CRUD matrix showing component access patterns
Data integration mapping (upstream sources, downstream consumers)
Data quality framework with measurable metrics
Requirements traceability (DR-xxx → Entity → Attribute)

Phase 5.7: Data Protection Impact Assessment

/arckit.dpia → Generate DPIA for UK GDPR Article 35 compliance

MANDATORY for high-risk processing - assess privacy risks before technology selection:

ICO 9-criteria automated screening (sensitive data, large scale, vulnerable subjects, AI/ML, etc.)
Auto-populated from data model (entities, PII, special category data, lawful basis)
Risk assessment focused on impact on individuals (privacy harm, discrimination)
Data subject rights implementation checklist (SAR, deletion, portability)
Children's data assessment (age verification, parental consent)
AI/ML algorithmic processing assessment (bias, explainability, human oversight)
ICO prior consultation flagging for high residual risks
International transfer safeguards (SCCs, BCRs, adequacy decisions)
Bidirectional links to risk register (DPIA-xxx risk IDs)
Links mitigations to Secure by Design security controls

Phase 5.8: Data Source Discovery

/arckit.datascout → Discover external data sources

Discover and evaluate external data sources to fulfil project data requirements:

Data needs extraction from DR/FR/INT/NFR requirements
UK Government open data portals (data.gov.uk, ONS, NHS Digital, Companies House, OS Data Hub)
Commercial API providers and data marketplaces
Free/freemium APIs and open source datasets
Weighted evaluation scoring (Requirements Fit, Data Quality, License & Cost, API Quality, Compliance, Reliability)
Gap analysis for unmet data needs
Data model impact assessment (new entities, attributes, sync strategy)
Requirements traceability (every DR-xxx mapped to a source or flagged as gap)
TCoP Point 10 compliance (Make Better Use of Data)

Phase 6: Technology Research

/arckit.research → Research technology, services, and products

Research available solutions to meet requirements with build vs buy analysis:

Dynamic category detection from requirements (authentication, payments, databases, etc.)
Commercial SaaS options with pricing, reviews, and ratings (WebSearch)
Open source alternatives with GitHub stats and community maturity
UK Government GOV.UK platforms (One Login, Pay, Notify, Forms)
Digital Marketplace suppliers (G-Cloud, DOS)
Total Cost of Ownership (TCO) comparison (3-year)
Build vs Buy vs Adopt recommendations
Vendor shortlisting for deeper evaluation
Integration with Wardley mapping (evolution positioning)
Feeds into SOBC Economic Case (cost data, options analysis)

Phase 6.5: Grants & Funding Research

/arckit.grants → Research UK government grants, charitable funding, and accelerator programmes

Identify and evaluate funding opportunities with eligibility scoring:

UK Innovate UK grants and R&D funding (e.g. Smart Grants, KTP, SBRI)
UK Research and Innovation (UKRI) funding calls
Charitable foundations and philanthropic funding (e.g. National Lottery Heritage Fund, Wellcome Trust)
Accelerator and incubator programmes (e.g. DCMS, DSIT-backed cohorts)
EU Horizon Europe successor funding open to UK entities
Eligibility scoring matrix against project requirements and stakeholder profile
Application timeline, deadlines, and award values
Strategic fit assessment (alignment with project goals and public sector context)
Outputs a structured GRNT funding opportunity register

Phase 7: Strategic Planning with Wardley Mapping

/arckit.wardley → Create strategic Wardley Maps

Visualize strategic positioning with:

Component evolution analysis (Genesis → Custom → Product → Commodity)
Build vs Buy decision framework
Vendor comparison and procurement strategy
UK Government Digital Marketplace mapping
Evolution predictions and strategic gameplay

Phase 7.5: Strategic Roadmap

/arckit.roadmap → Create multi-year architecture roadmap

Create strategic roadmap for multi-year transformation programs:

Multi-year timeline: 3-5 year roadmap with Mermaid Gantt chart aligned to financial years (FY 2024/25, etc.)
Strategic themes: Cloud migration, data modernization, security & compliance, DevOps transformation
Capability evolution: Maturity progression from L1 (Initial) to L5 (Optimized) over time
Investment planning: CAPEX/OPEX budget by financial year, ROI projections, benefits realization
Governance framework: ARB monthly, Programme Board monthly, Steering Committee quarterly
Service Standard gates: Alpha/Beta/Live assessment milestones (UK Government)
Dependencies: Mermaid flowchart showing initiative sequencing and critical path
Success metrics: Cloud adoption %, technical debt reduction, deployment frequency, time to market
Traceability: Links roadmap themes to stakeholder drivers, architecture principles, requirements
UK Government specifics: Spending Review alignment, TCoP compliance timeline, NCSC CAF progression

Use this when: You have a multi-year transformation program with multiple initiatives running in parallel. Roadmaps are strategic (multi-year, multi-initiative, executive communication) vs project plans which are tactical (single initiative, detailed tasks, team execution).

Roadmap feeds into: /arckit.plan for detailed phase execution, /arckit.sobc for investment business case, /arckit.backlog for prioritized user stories, /arckit.strategy for executive-level synthesis.

Phase 7.6: Architecture Strategy Synthesis

/arckit.strategy → Synthesise strategic artifacts into executive-level Architecture Strategy

Create a comprehensive Architecture Strategy document that synthesises multiple strategic artifacts into a single coherent narrative:

Strategic vision: 2-3 paragraphs articulating the transformation vision and success definition
Strategic drivers: Summarised from stakeholder analysis with external drivers (regulatory, market, technology)
Guiding principles: Key principles with strategic implications, compliance summary
Current state assessment: Technology landscape, capability maturity baseline (L1-L5), technical debt, SWOT
Target state vision: Future architecture, capability maturity targets, architecture vision diagram
Technology evolution: Build vs buy decisions, technology radar (Adopt/Trial/Assess/Hold) from Wardley maps
Strategic themes: 3-5 investment themes with objectives, initiatives, success criteria, principles alignment
Delivery roadmap summary: Timeline, phases, milestones from roadmap artifact
Investment summary: CAPEX/OPEX, NPV, IRR, payback period, benefits realisation from SOBC
Strategic risks: Top risks with heat map, assumptions, constraints from risk register
Success metrics: KPIs with baselines and year-over-year targets
Governance model: Forums, decision rights, review cadence
Traceability: Driver → Goal → Outcome → Theme → Principle → KPI chain

Use this when: You have multiple strategic artifacts (principles, stakeholders, wardley, roadmap, sobc) and need to create a single executive-level document that synthesises them into a coherent strategy. Ideal for Strategy Board presentations, executive briefings, or stakeholder communication.

Unique requirement: This is the only ArcKit command with TWO mandatory inputs (principles AND stakeholders). Strategy cannot be created without understanding both the decision framework and the stakeholder drivers.

Strategy feeds into: /arckit.requirements for detailed requirements, /arckit.roadmap for expanded timeline, /arckit.plan for project delivery.

Phase 7.7: Architecture Decision Records

/arckit.adr → Document architectural decisions

Create Architecture Decision Records (ADRs) following MADR v4.0 format enhanced with UK Government requirements:

Decision metadata: Sequential numbering (ADR-001, ADR-002), status (Proposed/Accepted/Superseded), escalation level (Team/Cross-team/Department/Cross-government)
Stakeholder RACI: Deciders (accountable), Consulted (SMEs, two-way), Informed (one-way communication)
Context and problem statement: Why this decision is needed, business/technical/regulatory drivers
Decision drivers: Technical forces (performance, security, scalability), business forces (cost, time), compliance forces (GDS Service Standard, TCoP, NCSC, UK GDPR)
Options analysis: Minimum 2-3 options plus "Do Nothing" baseline, each with pros/cons, cost (CAPEX/OPEX/TCO), GDS Service Standard impact, Wardley evolution stage
Y-Statement: Structured justification - "In the context of X, facing Y, we decided for Z to achieve A, accepting B"
Consequences: Positive (benefits, capabilities), Negative (trade-offs, technical debt), Neutral (training, infrastructure), Risks and mitigations
Validation: How implementation will be verified (design reviews, code reviews, testing, monitoring)
Traceability: Links to requirements, principles, stakeholders, research, Wardley maps, diagrams, risk register
UK Government specifics: Escalation levels (Team → Cross-team → Department → Cross-government), governance forums (ARB, TDA, Programme Board), Service Standard/TCoP compliance documentation

Use this when: Making significant architectural decisions that affect system structure, quality attributes, or behavior - technology choices (databases, frameworks, cloud services), integration patterns, security approaches, deployment strategies, data management.

ADR feeds into: /arckit.diagram (architecture diagrams reflect decisions), /arckit.hld-review and /arckit.dld-review (reviews verify decisions implemented), /arckit.traceability (decisions are key traceability artifacts).

Phase 8: Vendor Procurement (if needed)

/arckit.sow → Generate Statement of Work (RFP)

Create RFP-ready documents with:

Scope of work and deliverables
Technical requirements
Vendor qualifications
Evaluation criteria
Contract terms

/arckit.dos → Digital Outcomes and Specialists (DOS) procurement 🇬🇧

For UK public sector organizations needing custom development:

Generate DOS-compliant procurement documentation
Extract requirements from project artifacts (BR/FR/NFR/INT/DR)
Essential vs desirable skills from requirements
Success criteria (technology-agnostic)
Evaluation framework (40% Technical, 30% Team, 20% Quality, 10% Value)
Audit-ready documentation for Digital Marketplace

/arckit.gcloud-search → G-Cloud service search with live marketplace search 🇬🇧

For UK public sector organizations needing off-the-shelf cloud services:

Generate G-Cloud requirements document
Live Digital Marketplace search using WebSearch
Find actual services with suppliers, prices, features, links
Service comparison table with recommendations
Shortlist top 3-5 matching services
Links to Digital Marketplace guidance (gov.uk)

/arckit.gcloud-clarify → G-Cloud service validation and gap analysis 🇬🇧

Validate G-Cloud services and generate supplier clarification questions:

Systematic gap analysis (MUST/SHOULD requirements vs service descriptions)
Detect gaps: ✅ Confirmed, ⚠️ Ambiguous, ❌ Not mentioned
Generate prioritised questions (🔴 Critical / 🟠 High / 🔵 Medium / 🟢 Low)
Risk assessment matrix for each service
Email templates for supplier engagement
Evidence requirements specification
Next steps checklist

/arckit.evaluate → Create vendor evaluation framework

Set up systematic scoring:

Technical evaluation criteria (100 points)
Cost evaluation methodology
Reference check templates
Decision matrix

/arckit.evaluate (compare mode) → Compare vendor proposals

Side-by-side analysis of:

Technical approaches
Cost breakdowns
Risk assessments
Value propositions

Phase 9: Design Review

/arckit.hld-review → Review High-Level Design

Validate designs against:

Architecture principles compliance
Requirements coverage
Security and compliance
Scalability and resilience
Operational readiness

/arckit.dld-review → Review Detailed Design

Implementation-ready validation:

Component specifications
API contracts (OpenAPI)
Database schemas
Security implementation
Test strategy

Phase 10: Sprint Planning

/arckit.backlog → Generate prioritised product backlog

Transform requirements into sprint-ready user stories:

Convert requirements (BR/FR/NFR/INT/DR) to GDS-format user stories
Multi-factor prioritization (MoSCoW + risk + value + dependencies)
Organise into sprint plan with capacity balancing
Generate traceability matrix (requirements → stories → sprints)
Export to Jira/Azure DevOps (CSV) or custom tools (JSON)
Time savings: 75%+ (4-6 weeks → 3-5 days)

When to run: After HLD approval, before Sprint 1 (Alpha → Beta transition)

Phase 10.5: Backlog Export

/arckit.trello → Export product backlog to Trello

Push your backlog directly to Trello for sprint execution:

Create Trello board with sprint-based lists (Product Backlog + per-sprint + In Progress + Done)
Cards with priority labels, story points, and acceptance criteria checklists
Colour-coded labels by MoSCoW priority and requirement type
Rate-limit-aware Trello API integration
Requires TRELLO_API_KEY and TRELLO_TOKEN environment variables

When to run: After /arckit.backlog generates the product backlog (requires JSON export)

Phase 11: ServiceNow Service Management Design

/arckit.servicenow → Generate ServiceNow service design

Bridge architecture to operations:

CMDB design (derived from architecture diagrams)
SLA definitions (derived from NFRs)
Incident management design
Change management plan
Monitoring and alerting plan
Service transition plan

Phase 12: Traceability

/arckit.traceability → Generate traceability matrix

Ensure complete coverage:

Requirements → Design mapping
Design → Test mapping
Gap analysis and orphan detection
Change impact tracking

Phase 13: Quality Assurance

/arckit.analyze → Comprehensive governance quality analysis

Periodically assess governance quality across all artifacts:

Architecture principles compliance
Requirements coverage and traceability
Stakeholder alignment verification
Risk management completeness
Design review quality
Documentation completeness and quality
Gap identification and recommendations

When to use: Run periodically (before milestones, design reviews, or procurement decisions) to identify gaps and ensure governance standards are maintained.

Phase 14: Compliance Assessment (UK Government)

For UK Government and public sector projects:

/arckit.service-assessment → GDS Service Standard assessment preparation

Prepare for mandatory GDS Service Standard assessments:

Analyze evidence against all 14 Service Standard points
Identify gaps for alpha, beta, or live assessments
Generate RAG (Red/Amber/Green) ratings and overall readiness score
Provide actionable recommendations with priorities and timelines
Include assessment day preparation guidance
Map ArcKit artifacts to Service Standard evidence requirements

Run at end of Discovery (for alpha prep), mid-Beta (for beta prep), or before Live to ensure readiness.

/arckit.tcop → Technology Code of Practice assessment

Assess compliance with all 13 TCoP points:

Point 1: Define user needs
Point 2: Make things accessible
Point 3: Be open and use open source
Point 4: Make use of open standards
Point 5: Use cloud first
Point 6: Make things secure
Point 7: Make privacy integral
Point 8: Share, reuse and collaborate
Point 9: Integrate and adapt technology
Point 10: Make better use of data
Point 11: Define your purchasing strategy
Point 12: Meet the Digital Spend Controls
Point 13: Define your responsible AI use

/arckit.secure → UK Government Secure by Design assessment

Security compliance assessment:

NCSC Cloud Security Principles
NCSC Cyber Assessment Framework (CAF)
Cyber Essentials / Cyber Essentials Plus
UK GDPR and DPA 2018 compliance
Security architecture review
Threat modeling

/arckit.ai-playbook → UK Government AI Playbook compliance (for AI systems)

Responsible AI assessment:

AI ethics principles
Transparency and explainability
Fairness and bias mitigation
Data governance for AI
Human oversight mechanisms
Impact assessment

/arckit.atrs → Algorithmic Transparency Recording Standard

Generate ATRS record for algorithmic decision-making:

Algorithm details and logic
Purpose and use case
Data sources and data quality
Performance metrics and monitoring
Impact assessment and mitigation

For MOD Projects:

/arckit.mod-secure → MOD Secure by Design assessment

MOD-specific security compliance:

JSP 440 (Defence Project & Programme Management)
Information Assurance Maturity Model (IAMM)
MOD Security clearances and vetting
STRAP classification handling
Security Operating Procedures (SyOPs)
Supplier attestation requirements

/arckit.jsp-936 → MOD JSP 936 AI Assurance Documentation

For defence projects using AI/ML systems:

JSP 936 (Dependable Artificial Intelligence in Defence)
5 Ethical Principles (Human-Centricity, Responsibility, Understanding, Bias & Harm Mitigation, Reliability)
5 Risk Classification Levels (Critical to Minor)
8 AI Lifecycle Phases (Planning to Quality Assurance)
Approval pathways (2PUS/Ministerial → Defence-Level → TLB-Level)
RAISOs and Ethics Manager governance
Human-AI teaming strategy and continuous monitoring

Phase 14.5: Compliance Assessment (EU and French Government)

ArcKit includes commands for EU regulatory compliance and French public sector governance. These commands are applicable to organisations operating in the EU or under French jurisdiction — whether public sector or private.

EU Regulations

/arckit.eu-rgpd → GDPR compliance assessment (Regulation 2016/679)

Assess personal data processing obligations:

Legal basis determination (consent, contract, legitimate interest, legal obligation)
Data subject rights implementation (access, erasure, portability, objection)
CNIL registration and DPO obligations (France)
Cross-border transfer safeguards (SCCs, BCRs, adequacy decisions)
Integration with DPIA (/arckit.dpia) for high-risk processing

/arckit.eu-ai-act → EU AI Act compliance (Regulation 2024/1689)

Assess AI system obligations under the EU's risk-based AI framework:

Risk classification (unacceptable / high-risk / limited-risk / minimal)
High-risk system obligations: conformity assessment, CE marking, EUDB registration
GPAI model obligations for providers of general-purpose AI
Human oversight, transparency, and fundamental rights impact assessment
Prohibited practices (social scoring, real-time biometric surveillance)

/arckit.eu-nis2 → NIS2 Directive compliance (Directive 2022/2555)

Assess cybersecurity obligations for essential and important entities:

Sector classification (Annex I Essential vs Annex II Important)
OIV/OSE designation under French transposition (LPM/LCEN)
Governance, risk management, and incident reporting obligations
Supply chain security and vulnerability disclosure
ANSSI notification timeline (24h → 72h → 30-day final report)

/arckit.eu-dora → DORA compliance (Regulation 2022/2554) for financial entities

Digital Operational Resilience Act obligations for banks, insurers, and investment firms:

ICT risk management framework (5 pillars)
Major ICT-related incident classification and reporting (4h → 72h → monthly final)
TLPT (Threat-Led Penetration Testing) requirements for significant institutions
Third-party ICT provider management and critical provider designation
Contractual requirements for ICT service agreements

/arckit.eu-cra → Cyber Resilience Act compliance (Regulation 2024/2847)

Mandatory cybersecurity requirements for products with digital elements (hardware + software):

Product classification (Default / Important Class I / Critical Class II)
12 Annex I Part I security-by-design requirements
SBOM in SPDX or CycloneDX format (mandatory)
Vulnerability Disclosure Policy and 24h ENISA reporting
Conformity assessment route (internal control vs notified body)
Full application deadline: 11 December 2027

/arckit.eu-dsa → EU Digital Services Act compliance (Regulation 2022/2065)

Tiered obligations for online intermediary services:

Provider classification (mere conduit / hosting / platform / VLOP / VLOSE)
VLOP/VLOSE designation threshold: 45M monthly active EU users
Content moderation, recommender system transparency, advertising obligations
ARCOM as French Digital Services Coordinator (DSC)
Systemic risk assessment and independent audit for VLOPs

/arckit.eu-data-act → EU Data Act compliance (Regulation 2023/2854)

Data sharing obligations for connected products and cloud providers:

Role determination: manufacturer / data holder / DAPS / public sector body
User data access rights (Chapter II) and B2B sharing (Chapter III)
Cloud switching obligations (Chapter VI) — egress fee elimination by September 2027
International data transfer restrictions (Article 27)
Application date: 12 September 2025

French Public Sector Governance

/arckit.fr-rgpd → French GDPR compliance with CNIL-specific requirements

Extends EU GDPR with French context:

CNIL enforcement priorities and sector-specific guidelines
French DPO registration and CNIL prior consultation obligations
Biometric data processing under French law (CNIL authorisation required)

/arckit.fr-ebios → EBIOS Risk Manager methodology (ANSSI 2018)

French standard risk analysis for IS homologation:

5-workshop structure (Framework, Risk Sources, Strategic Scenarios, Operational Scenarios, Risk Treatment)
OIV/OSE/public sector IS homologation evidence
Attack path modelling and feared events
Integration with PSSI and SecNumCloud qualification

/arckit.fr-anssi → ANSSI 42 Cybersecurity Hygiene Measures assessment

Assess compliance with ANSSI's foundational hygiene guide:

7 themes: administration, authentication, updates, monitoring, backups, network, workstations
Cloud security recommendations (ANSSI cloud qualification matrix)
Gap analysis with prioritised remediation (P1–P3)
Integration with EBIOS and PSSI

/arckit.fr-anssi-carto → ANSSI SI Cartography (4-level IS mapping)

Generate structured IS cartography following ANSSI's 4-level methodology:

Level 1: Business processes and core missions
Level 2: Application and data mapping
Level 3: Server, database, and system inventory
Level 4: Network topology, firewall rules, interconnections
Attack surface summary and sensitive flow identification

/arckit.fr-secnumcloud → SecNumCloud qualification assessment

Assess cloud provider and customer obligations under ANSSI's SecNumCloud referential:

Visa vs qualification distinction (only full qualification satisfies OIV/ministerial use)
IS homologation prerequisites for SecNumCloud deployment
SecNumCloud-compatible architecture requirements
Procurement clauses for public-cloud contracts

/arckit.fr-dinum → DINUM digital doctrine assessment

Assess compliance with French digital government doctrine:

RGI (Référentiel Général d'Interopérabilité) — interoperability standards
RGAA (Référentiel Général d'Amélioration de l'Accessibilité) — accessibility
Doctrine cloud (cloud native, cloud first, SecNumCloud for sensitive data)
SILL (Socle Interministériel de Logiciels Libres) — recommended open source stack

/arckit.fr-marche-public → French public procurement (Code de la Commande Publique)

Generate procurement documentation compliant with French public contract law:

Marché public thresholds and procedures (below/above EU thresholds)
CCAP, CCTP, RC documentation templates
ANSSI-qualified provider requirements (PASSI, PRIS, PDIS)
Achat public durable obligations (environmental and social clauses)

/arckit.fr-pssi → PSSI (Politique de Sécurité des Systèmes d'Information)

Generate IS security policy for French public sector entities:

9-section structure approved by the Highest Authority (AA)
7 security domains (network, workstations, applications, IS management, physical, personnel, continuity)
RSSI, DPO, DSI, and FSSI roles
Review cycle and integration with EBIOS and homologation

/arckit.fr-dr → Diffusion Restreinte (DR) handling compliance

Assess document and IS handling requirements under the DR administrative classification:

II 901/SGDSN rules for DR document lifecycle
Electronic storage, transmission, and physical handling obligations
IS homologation for DR-processing systems
Scope explicitly bounded: DR only — IGI 1300 (Confidentiel Défense and above) is out of scope

/arckit.fr-algorithme-public → French Public Algorithm Transparency Notice

Generate mandatory transparency notice under CRPA Art. L311-3-1:

Scope determination: which automated decisions are covered
Plain-language description per algorithm, parameters, and weights
Human oversight mechanisms and appeal rights
GDPR Art. 22 intersection (automated individual decisions)
EU AI Act flagging for ML-based systems
More legally binding than the UK ATRS equivalent

/arckit.fr-code-reuse → French Public Code Reuse Assessment (Circulaire 2021-1524)

Assess code reuse obligations before building or procuring:

code.gouv.fr search (French public code catalogue)
SILL (Socle Interministériel de Logiciels Libres) — ministerially recommended open source
EU public code alternatives (Joinup, European Commission repositories)
Licence compatibility matrix (EUPL-1.2 recommended for public code publication)
Decision matrix: reuse / fork / SILL adoption / procure / build
Circulaire 2021 publication obligation: modified public code must be released back

Phase 15: Project Story & Reporting

/arckit.story → Generate comprehensive project story

Create narrative historical record with complete timeline analysis:

Timeline Analysis: 4 visualization types (Gantt chart, linear flowchart, detailed table, phase duration pie chart)
Timeline Metrics: Project duration, velocity, phase analysis, critical path identification
Complete Timeline: All events from git log or file modification dates with days-from-start
8 Narrative Chapters: Foundation → Business Case → Requirements → Research → Procurement → Design → Delivery → Compliance
Traceability Demonstration: End-to-end chains with Mermaid diagrams showing stakeholder → goals → requirements → stories → sprints
Governance Achievements: Showcase compliance (TCoP, Service Standard, NCSC CAF), risk management, decision rationale
Strategic Context: Wardley Map insights, build vs buy decisions, vendor selection rationale
Lessons Learned: Pacing analysis, timeline deviations, recommendations for future projects
Comprehensive Appendices: Artifact register, chronological activity log, DSM, command reference, glossary

When to use: At project milestones or completion to create shareable story for stakeholders, leadership, or portfolio reporting. Perfect for demonstrating systematic governance and ArcKit workflow value.

/arckit.presentation → Generate MARP slide deck from project artifacts

Create presentation slides from existing architecture artifacts:

MARP Format: Markdown-based slides with --- separators — exports to PDF, PPTX, or HTML
Focus Modes: Executive (board-level), Technical (architecture detail), Stakeholder (benefits-focused), Procurement (RFP briefings)
Artifact-Driven: Reads all available project artifacts and extracts key content into slides
Mermaid Diagrams: Gantt charts, C4 diagrams, pie charts, and quadrant charts embedded natively
Configurable: Choose slide count (6-8, 10-12, 15-20) and MARP theme (default, gaia, uncover)
Doc type code: PRES

When to use: Before governance boards, stakeholder briefings, gate reviews, or quarterly portfolio presentations. Run after creating most project artifacts for the richest slide deck.

Phase 16: Documentation Publishing

/arckit.pages → Generate documentation site

Publish all project documentation as an interactive website:

Static Site Generation: Generates docs/index.html and docs/manifest.json — deployable to any static host (GitHub Pages, Netlify, Vercel, S3, etc.)
Mermaid Diagram Rendering: All architecture diagrams render inline with mermaid.js
Project Navigation: Sidebar with collapsible project tree, document categories, and version badges — documents with multiple versions show an inline dropdown selector
GOV.UK Styling: Professional government design system styling
Document Index: Manifest.json provides programmatic access to all artifacts
LLM Discovery: Generates docs/llms.txt (llmstxt.org format) so LLM agents and crawlers can index every artifact, guide, and project. Hand-curated docs/llms.txt files (without the ArcKit generation marker) are preserved on re-runs

When to use: When you want to share project documentation with stakeholders via a professional web interface, or to create a portfolio view of all architecture artifacts.

Supported AI Assistants

Assistant	Support	Notes
Claude Code	✅ Premier	Primary platform. Plugin with agents, hooks, MCP servers, and auto-updates
Gemini CLI	✅ Full	Extension with commands, MCP servers, and auto-updates
GitHub Copilot	✅ Core	VS Code prompt files, custom agents, and repo-wide instructions (`arckit init --ai copilot`)
OpenAI Codex CLI	✅ Core	CLI with commands and templates. ChatGPT Plus/Pro/Enterprise (Setup Guide)
OpenCode CLI	✅ Core	CLI with commands and templates

Platform Support: ArcKit is developed and tested on Linux. Windows has limited support — hooks (session init, project context, filename validation, MCP auto-allow) require bash and jq which are not available on stock Windows. For the best experience on Windows, use a devcontainer or WSL2.

Why Claude Code?

Claude Code is the primary development platform for ArcKit and provides capabilities not available in other formats:

Feature	Claude Code	Gemini CLI	Copilot	Codex / OpenCode
70 cross-AI slash commands (plus 46 community-contributed)	✅	✅	✅	✅
`/arckit:build` parallel build harness (Claude-only — depends on parallel `Agent` dispatch)	✅	—	—	—
Templates & scripts	✅	✅	✅	✅
Bundled MCP servers (AWS, Azure, GCP, DataCommons, govreposcrape)	✅	✅ (3 servers)	—	Manual setup
Autonomous research agents (10 agents for research, datascout, cloud research, gov code discovery, grants, framework)	✅	—	✅ (10 agents)	—
SessionStart hook (auto-detect version + projects)	✅	—	—	—
UserPromptSubmit hook (project context injection on every prompt)	✅	—	—	—
PreToolUse hook (ARC filename auto-correction)	✅	—	—	—
PermissionRequest hook (auto-allow MCP documentation tools)	✅	—	—	—
Per-command Stop hooks (output validation, e.g. Wardley Map math checks)	✅	—	—	—
Wardley Mapping skill (with Pinecone MCP book corpus)	✅	—	—	—
Mermaid Syntax Reference skill (23 diagram types + config)	✅	✅	—	✅
Automatic marketplace updates	✅	✅	Manual reinstall	Manual reinstall
Zero-config installation	✅	✅	`arckit init` required	`arckit init` required

Agents run research-heavy commands (market research, data source discovery, cloud service evaluation) in isolated context windows, keeping the main conversation clean and enabling dozens of WebSearch/WebFetch/MCP calls without context bloat.

Hooks provide automated governance: filenames are auto-corrected to ArcKit conventions, project context is injected into every prompt so commands know what artifacts exist, MCP tools are auto-approved, and generated outputs like Wardley Maps are validated for mathematical consistency before being finalized.

Gemini CLI provides a strong experience with all commands and MCP servers but lacks agent delegation and hooks. GitHub Copilot provides all 70 official commands (plus 46 community-contributed overlays) as prompt files and 10 custom agents but lacks hooks and MCP servers. Codex CLI and OpenCode CLI provide core command functionality but require manual setup and arckit init scaffolding.

Why Commands, Not Skills

Claude Code automatically exposes ArcKit commands as skills (they appear in the skills list and can be matched by natural language). ArcKit intentionally uses slash commands rather than standalone skills because:

Deliberate invocation required — Every command generates a heavyweight governance document (requirements spec, risk register, DPIA, etc.). Auto-triggering from conversational intent would waste significant time and tokens.
Dependency ordering — Commands follow a deliberate sequence (principles → stakeholders → requirements → data-model → etc.). Skills that auto-trigger could run out of order.
User input via $ARGUMENTS — Most commands accept context from the user (project name, scope, constraints). The command system handles this with $ARGUMENTS substitution.
Best of both worlds — Since Claude Code exposes commands as skills automatically, users get explicit /arckit.requirements invocation AND natural language matching when Claude recognises intent — no restructuring needed.

Using with GitHub Copilot

For GitHub Copilot users in VS Code, ArcKit commands are delivered as prompt files and custom agents:

# Install and create project (3 steps, zero config)
pip install git+https://github.com/tractorjuice/arc-kit.git
arckit init my-project --ai copilot
cd my-project && code .

# Then use ArcKit commands in Copilot Chat
/arckit-principles Create principles for financial services
/arckit-stakeholders Analyze stakeholders for cloud migration
/arckit-requirements Create comprehensive requirements

This creates .github/prompts/arckit-*.prompt.md (67 prompt files), .github/agents/arckit-*.agent.md (9 custom agents), and .github/copilot-instructions.md (repo-wide context).

Using with Codex CLI

For OpenAI Codex CLI users, ArcKit commands are delivered as skills and auto-discovered:

# Install and create project (3 steps, zero config)
pip install git+https://github.com/tractorjuice/arc-kit.git
arckit init my-project --ai codex
cd my-project && codex

# Then use ArcKit skills
$arckit-principles Create principles for financial services
$arckit-stakeholders Analyze stakeholders for cloud migration
$arckit-requirements Create comprehensive requirements

See .codex/README.md for full Codex CLI setup and usage.

Project Structure

ArcKit creates this structure:

payment-modernization/
├── .arckit/
│   ├── scripts/
│   │   └── bash/                          # Automation scripts
│   ├── templates/                         # Default templates (refreshed by arckit init)
│   └── templates-custom/                  # Your customizations (preserved across updates)
├── projects/
│   ├── 000-global/
│   │   └── ARC-000-PRIN-v1.0.md          # Global principles
│   └── 001-payment-gateway/
│       ├── ARC-001-STKE-v1.0.md           # Stakeholder analysis
│       ├── ARC-001-RISK-v1.0.md           # Risk register (Orange Book)
│       ├── ARC-001-SOBC-v1.0.md           # Strategic Outline Business Case
│       ├── ARC-001-REQ-v1.0.md            # Comprehensive requirements
│       ├── ARC-001-DATA-v1.0.md           # Data model with ERD, GDPR compliance
│       ├── wardley-maps/                   # Strategic Wardley Maps
│       │   ├── ARC-001-WARD-001-v1.0.md   # Current architecture positioning
│       │   ├── ARC-001-WARD-002-v1.0.md   # Target architecture vision
│       │   ├── ARC-001-WARD-003-v1.0.md   # Gap analysis
│       │   └── ARC-001-WARD-004-v1.0.md   # Build vs buy decisions
│       ├── ARC-001-SOW-v1.0.md            # Statement of Work (RFP)
│       ├── ARC-001-EVAL-v1.0.md           # Vendor evaluation framework
│       ├── vendors/
│       │   ├── acme-corp/
│       │   │   ├── proposal.pdf
│       │   │   ├── scoring.md
│       │   │   ├── hld-v1.md
│       │   │   └── reviews/
│       │   │       └── hld-v1-review.md
│       │   ├── beta-systems/
│       │   │   └── ...
│       │   └── comparison.md
│       ├── ARC-001-SNOW-v1.0.md           # Service management design
│       ├── ARC-001-TRAC-v1.0.md           # Traceability matrix
│       └── final/
│           ├── selected-vendor.md
│           ├── approved-hld.md
│           └── dld/
├── .agents/skills/                        # Codex CLI skills (auto-discovered)
├── .codex/
│   ├── agents/                            # Agent configs
│   └── config.toml                        # MCP servers + agent roles
├── .github/
│   ├── prompts/arckit-*.prompt.md         # GitHub Copilot prompt files (70 official + community overlays)
│   ├── agents/arckit-*.agent.md           # GitHub Copilot custom agents (10 agents)
│   └── copilot-instructions.md            # Repo-wide Copilot context
└── .opencode/commands/                    # OpenCode CLI commands

Template Customization

Customize ArcKit templates without modifying defaults:

# Inside your AI assistant
/arckit.customize requirements   # Copy requirements template for editing
/arckit.customize all            # Copy all templates
/arckit.customize list           # See available templates

How it works:

Default templates live in .arckit/templates/ (refreshed by arckit init)
Your customizations go in .arckit/templates-custom/ (preserved across updates)
Commands automatically check for custom templates first, falling back to defaults

Common customizations:

Add organization-specific document control fields
Include mandatory compliance sections (ISO 27001, PCI-DSS)
Add department-specific approval workflows
Customize UK Government classification banners

Complete Command Reference

All 67 ArcKit commands with maturity status and example outputs from public test repositories (43 public test repos across v0–v48).

Status Legend

Status	Description
🟢 Live	Production-ready, extensively tested
🔵 Beta	Feature-complete, actively refined
🟠 Alpha	Working, limited testing
🟣 Experimental	New in v0.11.x, early adopters

Example Repositories

Code	Repository	Description
v1	arckit-test-project-v1-m365	Microsoft 365 GCC-H Migration
v2	arckit-test-project-v2-hmrc-chatbot	HMRC Tax Assistant Chatbot
v3	arckit-test-project-v3-windows11	Windows 11 Enterprise Deployment
v6	arckit-test-project-v6-patent-system	IPO Patent Application System
v7	arckit-test-project-v7-nhs-appointment	NHS Appointment Booking
v8	arckit-test-project-v8-ons-data-platform	ONS Data Platform Modernisation
v9	arckit-test-project-v9-cabinet-office-genai	Cabinet Office GenAI Platform
v10	arckit-test-project-v10-training-marketplace	UK Government Training Marketplace
v11	arckit-test-project-v11-national-highways-data	National Highways Data Architecture
v14	arckit-test-project-v14-scottish-courts	Scottish Courts GenAI Strategy
v16	arckit-test-project-v16-doctors-appointment	Doctors Online Appointment System
v17	arckit-test-project-v17-fuel-prices	UK Government Fuel Price Transparency Service
v18	arckit-test-project-v18-smart-meter	UK Smart Meter Data Consumer App
v19	arckit-test-project-v19-gov-api-aggregator	UK Government API Aggregator
v21	arckit-test-project-v21-criminal-courts	Independent Review of the Criminal Courts — Tech & AI
v22	arckit-test-project-v22-genai-playbook	UK Government GenAI Playbook
v23	arckit-test-project-v23-ccs-procurement-ai	CCS AI Procurement Intelligence Platform
v24	arckit-test-project-v24-cabinet-office-ai	Cabinet Office Cross-Government AI Governance
v25	arckit-test-project-v25-dbt-trade-ai	DBT International Trade AI Analytics
v26	arckit-test-project-v26-dfe-education-ai	DfE AI in Education Governance & Standards
v27	arckit-test-project-v27-defra-environment-ai	DEFRA Environmental AI & Ecological Data
v28	arckit-test-project-v28-desnz-energy-ai	DESNZ Energy Grid AI & Net Zero Modelling
v29	arckit-test-project-v29-dhsc-health-ai	DHSC Health & Social Care AI Governance
v30	arckit-test-project-v30-dluhc-planning-ai	DLUHC Planning & Housing Data Intelligence
v31	arckit-test-project-v31-dsit-responsible-ai	DSIT Responsible AI & Innovation Standards
v32	arckit-test-project-v32-dft-transport-ai	DfT Transport Network AI & Journey Intelligence
v33	arckit-test-project-v33-dwp-benefits-ai	DWP Benefits Processing AI & Employment Intelligence
v34	arckit-test-project-v34-fcdo-diplomatic-ai	FCDO Diplomatic Intelligence & Consular AI
v35	arckit-test-project-v35-gld-legal-ai	GLD Legal AI & Litigation Intelligence
v36	arckit-test-project-v36-hmlr-land-ai	HMLR Land Registration AI & Property Intelligence
v37	arckit-test-project-v37-hmrc-tax-ai	HMRC Tax Compliance AI & Revenue Intelligence
v38	arckit-test-project-v38-hmt-fiscal-ai	HMT Fiscal Modelling AI & Economic Intelligence
v39	arckit-test-project-v39-home-office-borders-ai	Home Office Borders, Immigration & Security AI
v40	arckit-test-project-v40-mod-defence-ai	MoD Defence AI Strategy & Operational Assurance
v41	arckit-test-project-v41-moj-justice-ai	MoJ Justice System AI & Court Innovation
v42	arckit-test-project-v42-no10-ds-policy-ai	No.10 Data Science Policy Intelligence Platform
v43	arckit-test-project-v43-iai-gov-ai-products	i.AI Government AI Products & Delivery
v44	arckit-test-project-v44-australian-gov	Australian Government — Architecture Governance (non-UK PoC)
v45	arckit-test-project-v45-nsi-rainbow	NS&I Digital Modernisation Programme (Project Rainbow)
v46	arckit-test-project-v46-gds-local	GDS Local
v46	arckit-test-project-v46-sdg	ArcKit SDG Mono-Repo (17 UN SDGs, 78 UK Gov projects)
v47	arckit-test-project-v47-dft-transforming-city-regions	DfT Transforming City Regions funding system
v48	arckit-test-project-v48-arckit-as-a-service	ArcKit as a Service for UK Government

Foundation

Command	Description	Examples	Status
`/arckit.init`	Initialize ArcKit project structure with numbered project directories and global artifacts	—	🟢 Live
`/arckit.start`	Get oriented with ArcKit — check project status, explore available commands, and choose your next step	—	🟢 Live
`/arckit.plan`	Create project plan with timeline, phases, gates, and Mermaid diagrams	v3/001 v3/002 v3/004 v3/005 v8 v9 v10 v11 v14 v17 v18	🟢 Live
`/arckit.principles`	Create or update enterprise architecture principles	v1 v2 v3 v6 v8 v9 v10 v11 v7 v14 v16 v17 v18 v19	🟢 Live

Strategic Context

Command	Description	Examples	Status
`/arckit.stakeholders`	Analyze stakeholder drivers, goals, and measurable outcomes	v1 v2 v3/001 v3/002 v3/003 v3/004 v3/005 v3/006 v3/007 v6 v8 v9 v10 v11 v14 v16 v17 v18 v19	🟢 Live
`/arckit.risk`	Create comprehensive risk register following HM Treasury Orange Book principles	v3/001 v3/002 v3/003 v3/004 v3/005 v3/006 v3/007 v8 v9 v11 v14 v16 v17 v18	🟢 Live
`/arckit.sobc`	Create Strategic Outline Business Case (SOBC) using UK Government Green Book 5-case model	v3/001 v3/002 v3/003 v3/004 v3/005 v3/007 v8 v9	🟢 Live

Requirements & Data

Command	Description	Examples	Status
`/arckit.requirements`	Create comprehensive business and technical requirements	v1 v2 v3/001 v3/002 v3/003 v3/004 v3/005 v3/006 v3/007 v6 v8 v9 v10 v11 v7 v14 v16 v17 v18 v19	🟢 Live
`/arckit.data-model`	Create comprehensive data model with entity relationships, GDPR compliance, and data governance	v3/001 v3/002 v8 v9 v10 v11 v14 v16 v17 v18	🟢 Live
`/arckit.data-mesh-contract`	Create federated data product contracts for mesh architectures with SLAs, governance, and interoperability guarantees	—	🟠 Alpha
`/arckit.dpia`	Generate Data Protection Impact Assessment (DPIA) for UK GDPR Article 35 compliance	v3 v8 v9 v14 v16 v17 v18	🔵 Beta

Research & Strategy

Command	Description	Examples	Status
`/arckit.platform-design`	Create platform strategy using Platform Design Toolkit (8 canvases for multi-sided ecosystems)	v8 v10	🟣 Experimental
`/arckit.research`	Research technology, services, and products to meet requirements with build vs buy analysis	v3/001 v3/002 v14 v17 v18	🔵 Beta
`/arckit.grants`	Research UK government grants, charitable funding, and accelerator programmes with eligibility scoring	—	🟣 Experimental
`/arckit.wardley`	Create strategic Wardley Maps for architecture decisions and build vs buy analysis	v3 v6 v11 v14	🟣 Experimental
`/arckit.wardley.value-chain`	Decompose user needs into value chains for Wardley Mapping	—	🟣 Experimental
`/arckit.wardley.doctrine`	Assess organizational doctrine maturity (4 phases, 40+ principles)	—	🟣 Experimental
`/arckit.wardley.gameplay`	Analyze strategic plays from 60+ gameplay patterns	—	🟣 Experimental
`/arckit.wardley.climate`	Assess 32 climatic patterns affecting mapped components	—	🟣 Experimental
`/arckit.strategy`	Synthesise strategic artifacts into executive-level Architecture Strategy document	—	🔵 Beta
`/arckit.roadmap`	Create strategic architecture roadmap with multi-year timeline, capability evolution, and governance	v3	🔵 Beta
`/arckit.framework`	Transform architecture artifacts into a structured, reusable framework with principles, patterns, and implementation guidance	—	🔵 Beta
`/arckit.adr`	Document architectural decisions with options analysis and traceability	v3/001 v3/002 v3/003 v3/004 v3/005 v3/007 v14	🔵 Beta

Cloud Research (MCP)

These commands use Model Context Protocol (MCP) servers to access authoritative cloud provider documentation in real-time. The Claude Code plugin bundles both MCP servers automatically. Gemini and Codex users need to install them separately.

Command	Description	Examples	Status
`/arckit.azure-research`	Research Azure services and architecture patterns using Microsoft Learn MCP	v3/001 v3/002 v14 v17 v18 v19	🟣 Experimental
`/arckit.aws-research`	Research AWS services and architecture patterns using AWS Knowledge MCP	v14 v17 v18 v19	🟣 Experimental
`/arckit.gcp-research`	Research Google Cloud services and architecture patterns using Google Developer Knowledge MCP	—	🟣 Experimental

Data Source Discovery

Command	Description	Examples	Status
`/arckit.datascout`	Discover external data sources (APIs, datasets, open data portals) to fulfil project requirements	v17 v18 v19	🟣 Experimental

Note: The Google Developer Knowledge MCP requires an API key (GOOGLE_API_KEY environment variable). See the GCP Research guide for setup instructions.

Government Code Discovery

These commands use the govreposcrape MCP server to search 24,500+ UK government repositories. The Claude Code plugin bundles the MCP server automatically. No API key required.

Command	Description	Examples	Status
`/arckit.gov-code-search`	Search 24,500+ UK government repositories using natural language	—	🟣 Experimental
`/arckit.gov-landscape`	Map the UK government code landscape for a domain	—	🟣 Experimental
`/arckit.gov-reuse`	Discover reusable UK government code before building from scratch	—	🟣 Experimental

Procurement

Command	Description	Examples	Status
`/arckit.sow`	Generate Statement of Work (SOW) / RFP document for vendor procurement	v1 v2 v3/001 v3/002 v3/003 v6	🟢 Live
`/arckit.dos`	Generate Digital Outcomes and Specialists (DOS) procurement documentation for UK Digital Marketplace	—	🟣 Experimental
`/arckit.gcloud-search`	Find G-Cloud services on UK Digital Marketplace with live search and comparison	v3 v14	🟣 Experimental
`/arckit.gcloud-clarify`	Analyze G-Cloud service gaps and generate supplier clarification questions	—	🟣 Experimental
`/arckit.evaluate`	Create vendor evaluation framework and score vendor proposals	v1 v2 v3/001 v3/002 v3/003 v3/005 v6	🟢 Live
`/arckit.score`	Score vendor proposals with structured storage, side-by-side comparison, sensitivity analysis, and audit trail	—	🔵 Beta

Design & Architecture

Command	Description	Examples	Status
`/arckit.diagram`	Generate architecture diagrams using Mermaid for visual documentation	v1 v3/001 v3/005 v3/007 v10 v14 v17 v19	🟢 Live
`/arckit.hld-review`	Review High-Level Design (HLD) against architecture principles and requirements	v3 v14	🔵 Beta
`/arckit.dld-review`	Review Detailed Design (DLD) for implementation readiness	—	🔵 Beta

Operations

Command	Description	Examples	Status
`/arckit.backlog`	Generate prioritised product backlog from ArcKit artifacts - convert requirements to user stories, organise into sprints	v3/001 v3/002 v3/003 v3/004 v9 v14 v17 v19	🔵 Beta
`/arckit.trello`	Export product backlog to Trello - create board, lists, cards with labels and checklists from backlog JSON	—	🟣 Experimental
`/arckit.servicenow`	Create comprehensive ServiceNow service design with CMDB, SLAs, incident management, and change control	v3	🔵 Beta
`/arckit.devops`	Create DevOps strategy with CI/CD pipelines, IaC, container orchestration, and developer experience	v14	🟣 Experimental
`/arckit.mlops`	Create MLOps strategy with model lifecycle, training pipelines, serving, monitoring, and governance	v14	🟣 Experimental
`/arckit.finops`	Create FinOps strategy with cloud cost management, optimization, governance, and forecasting	v14	🟣 Experimental
`/arckit.operationalize`	Create operational readiness pack with support model, runbooks, DR/BCP, on-call, and handover documentation	v14	🟣 Experimental
`/arckit.traceability`	Generate requirements traceability matrix from requirements to design to tests	v1 v2 v3/001 v3/002 v3/003 v6 v9 v14	🟢 Live

Quality & Governance

Command	Description	Examples	Status
`/arckit.analyze`	Perform comprehensive governance quality analysis across architecture artifacts	v6 v9 v11 v14	🔵 Beta
`/arckit.principles-compliance`	Assess compliance with architecture principles and generate scorecard with evidence, gaps, and recommendations	v3 v14	🟢 Live
`/arckit.story`	Generate comprehensive project story with timeline analysis, traceability, and governance achievements	v3 v8 v9 v14	🟢 Live
`/arckit.presentation`	Generate MARP slide deck from project artifacts for governance boards and stakeholder briefings	—	🔵 Beta
`/arckit.conformance`	Assess architecture conformance — ADR decision implementation, cross-decision consistency, architecture drift, technical debt, and custom constraint rules	—	🔵 Beta
`/arckit.health`	Scan projects for stale research, forgotten ADRs, unresolved review conditions, orphaned requirements, missing traceability, and version drift	—	🔵 Beta
`/arckit.impact`	Analyse blast radius of changes — reverse dependency tracing	—	🟣 Experimental
`/arckit.search`	Search across all project artifacts by keyword, document type, or requirement ID	—	🔵 Beta
`/arckit.navigator`	Project-level GPS — show coverage against the essential ArcKit baseline, surface DRAFT/stale/orphan artifacts, and recommend the next slash command to run	—	🟢 Live
`/arckit.graph-report`	Governance metrics dashboard — coverage by category, cross-reference density, compliance readiness, and project comparison across all working projects	—	🟢 Live
`/arckit.customize`	Copy templates to `.arckit/templates-custom/` for customization (preserved across updates)	—	🟢 Live
`/arckit.maturity-model`	Generate capability maturity model with current-state assessment, target-state definition, and improvement roadmap	—	🔵 Beta
`/arckit.template-builder`	Create new document templates through interactive interview — generates community-origin templates, guides, and optional shareable bundles	—	🟠 Alpha

UK Government

Command	Description	Examples	Status
`/arckit.service-assessment`	Prepare for GDS Service Standard assessment - analyze evidence against 14 points, identify gaps, generate readiness report	v16	🔵 Beta
`/arckit.tcop`	Generate a Technology Code of Practice (TCoP) review document for a UK Government technology project	v6 v8 v9 v11 v14	🔵 Beta
`/arckit.secure`	Generate a Secure by Design assessment for UK Government projects (civilian departments)	v8 v9 v11 v14 v16 v17 v18 v19	🔵 Beta
`/arckit.ai-playbook`	Assess UK Government AI Playbook compliance for responsible AI deployment	v9 v14	🟠 Alpha
`/arckit.atrs`	Generate Algorithmic Transparency Recording Standard (ATRS) record for AI/algorithmic tools	v2 v9 v14	🟠 Alpha

UK MOD

Command	Description	Examples	Status
`/arckit.mod-secure`	Generate a MOD Secure by Design assessment for UK Ministry of Defence projects using CAAT and continuous assurance	v3/001 v3/006	🟣 Experimental
`/arckit.jsp-936`	Generate MOD JSP 936 AI assurance documentation for defence AI/ML systems	—	🟣 Experimental

Documentation & Publishing

Command	Description	Examples	Status
`/arckit.glossary`	Generate comprehensive project glossary with terms, definitions, acronyms, and cross-references	—	🔵 Beta
`/arckit.pages`	Generate documentation site with Mermaid diagram support	v1 v2 v3 v6 v7 v8 v9 v10 v11 v14 v16 v17 v18 v19	🟠 Alpha

Wardley Mapping for Strategic Architecture

ArcKit uses Wardley Maps to expose the strategic position of every component before you commit to a solution. The /arckit.wardley command produces ready-to-visualise maps that:

Trace user needs through the supporting value chain so gaps and duplicated effort are obvious.
Plot evolution from Genesis → Commodity to reveal when to build, buy, reuse, or retire capabilities.
Feed procurement, vendor evaluation, and design reviews with shared situational awareness.

Maps are emitted in the Open Wardley Map format — paste them straight into https://create.wardleymaps.ai for a visual view. Full example outputs live in the public demos such as arckit-test-project-v3-windows11 (enterprise OS rollout strategy) and arckit-test-project-v14-scottish-courts (GenAI platform strategy).

Architecture Diagrams with Mermaid

ArcKit generates visual architecture diagrams using Mermaid for clear technical communication.

What are Architecture Diagrams?

Architecture diagrams visualize system structure, interactions, and deployment for:

Technical Communication: Share architecture with stakeholders
Design Documentation: Document current and future state
Vendor Evaluation: Compare vendor technical approaches
UK Government Compliance: Visualize Cloud First, GOV.UK services, PII handling

Diagram Types

ArcKit supports 6 essential diagram types based on the C4 Model and enterprise architecture best practices:

Diagram Type	Level	Purpose	When to Use
C4 Context	Level 1	System in context with users and external systems	After requirements, to show system boundaries
C4 Container	Level 2	Technical containers and technology choices	After HLD, for vendor review
C4 Component	Level 3	Internal components within a container	After DLD, for implementation
Deployment	Infrastructure	Cloud resources and network topology	Cloud First compliance, cost estimation
Sequence	Interaction	API flows and request/response patterns	Integration requirements, API design
Data Flow	Data	How data moves, PII handling, GDPR compliance	UK GDPR, DPIA requirements

Use /arckit.diagram directly, or supply an explicit type such as context, container, sequence, or dataflow. Outputs bundle component inventories with Wardley evolution tags, built-in GOV.UK compliance scaffolding (Notify, Pay, Design System), Cloud First network patterns, GDPR annotations, and traceability back to requirements and tests. For full examples, browse the diagram folders in arckit-test-project-v3-windows11 and arckit-test-project-v14-scottish-courts.

ServiceNow Service Management Design

ArcKit turns architecture artefacts into an operations-ready ServiceNow pack. The /arckit.servicenow command builds:

CMDB hierarchies, SLAs, and change risk straight from requirements, diagrams, and Wardley Maps.
ITIL-aligned runbooks covering incident, change, monitoring, and transition activities.
UK government extras such as GDS Service Standard, Technology Code of Practice, and GOV.UK Pay/Notify dependencies when relevant.

For full outputs, explore the public demos (for example arckit-test-project-v3-windows11) where the generated ServiceNow design files and checklists are published end-to-end.

Documentation

Key references live in docs/ and top-level guides:

Quick tour: docs/index.html mirrors the public landing page.
Lifecycle visuals: WORKFLOW-DIAGRAMS.md and DEPENDENCY-MATRIX.md cover command flow and relationships.
Core guides: docs/guides/principles.md, docs/guides/requirements.md, docs/guides/procurement.md, docs/guides/design-review.md.
Traceability: docs/guides/traceability.md documents end-to-end coverage patterns.
DDaT Role Guides: docs/guides/roles/ — 18 guides mapping ArcKit commands to UK Government DDaT Capability Framework roles (Enterprise Architect, Solution Architect, Product Manager, etc.).

Comparison to Other Tools

Feature	ArcKit	Sparx EA	Ardoq	LeanIX	Confluence
AI-Assisted	✅	❌	❌	❌	❌
Wardley Mapping	✅	❌	⚠️ Limited	❌	❌
Version Control	✅ Git	❌	❌	❌	⚠️ Limited
Vendor RFP	✅	❌	❌	❌	⚠️ Manual
Design Review Gates	✅	⚠️ Manual	❌	❌	⚠️ Manual
Traceability	✅ Automated	⚠️ Manual	✅	⚠️ Limited	❌
Cost	Free	$$$$	$$$$	$$$$	$$
Learning Curve	Low	High	Medium	Medium	Low

Requirements

Python 3.11+
Git (optional but recommended)
AI Coding Agent: Claude Code v2.1.129+ (via plugin), Gemini CLI (via extension), OpenCode CLI (via CLI), or OpenAI Codex CLI (via CLI)
uv for package management: Install uv

Installation from Source

# Clone the repository
git clone https://github.com/tractorjuice/arc-kit.git
cd arc-kit

# Install in development mode
pip install -e .

# Run the CLI
arckit init my-project

Documentation

Full guidance lives in docs/ and the static site.

Quick tour: docs/index.html (mirrors the public landing page).
Core guides: docs/guides/principles.md, docs/guides/requirements.md, docs/guides/procurement.md, docs/guides/design-review.md.
Reference packs: WORKFLOW-DIAGRAMS.md and DEPENDENCY-MATRIX.md cover lifecycle visualisations and the 67×67 command matrix.
Traceability: docs/guides/traceability.md documents end-to-end requirements coverage.

Relationship to Spec Kit

ArcKit is inspired by Spec Kit but targets a different audience:

	Spec Kit	ArcKit
Audience	Product Managers, Developers	Enterprise Architects, Procurement
Focus	Feature development (0→1 code generation)	Architecture governance & vendor management
Workflow	Spec → Plan → Tasks → Code	Requirements → RFP → Design Review → Traceability
Output	Working code	Architecture documentation & governance

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Areas we need help:

Integration with enterprise tools (Jira, Azure DevOps)
Additional AI agent support
Template improvements based on real-world usage
Documentation and examples
ServiceNow API integration for automated CI creation

Tips

Continuous Governance Monitoring

Use the /loop command to run health checks on a recurring interval during long architecture sessions:

/loop 30m /arckit.health SEVERITY=HIGH

This runs /arckit.health every 30 minutes, surfacing stale research, forgotten ADRs, and unresolved review conditions as they appear.

Troubleshooting

Token Limit Error

If you see: API Error: Claude's response exceeded the 32000 output token maximum

The Problem: ArcKit generates large documents that can exceed Claude's 32K token output limit.

⚠️ IMPORTANT: Your Claude subscription plan determines the maximum tokens:

🔴 Free/Pro plans: 32K max (cannot be increased)
✅ Team/Enterprise plans: Can increase to 64K via environment variable

Solutions:

For Team/Enterprise plans - Increase token limit:
```
export CLAUDE_CODE_MAX_OUTPUT_TOKENS=64000
```
For ALL plans (including Free/Pro) - Use Write tool strategy:
```
User: /arckit.requirements but write directly to file using Write tool, show me only a summary
```
This tells Claude to use the Write tool to create the file (doesn't count toward output tokens) and only show you a summary.

Which commands are affected?

🔴 HIGH RISK: /arckit.sobc, /arckit.requirements, /arckit.data-model, /arckit.sow
🟢 MITIGATED (agent): /arckit.research, /arckit.datascout, /arckit.aws-research, /arckit.azure-research, /arckit.gcp-research, /arckit.gov-reuse, /arckit.gov-code-search, /arckit.gov-landscape, /arckit.grants — run as autonomous agents in separate context windows
🟡 MEDIUM RISK: /arckit.risk, /arckit.evaluate, /arckit.principles

See full guide: docs/TOKEN-LIMITS.md

Common Issues

Command not found: Ensure commands are available

# For Codex, check if skills directory exists
ls .agents/skills/arckit-principles/SKILL.md

# For Claude Code, install the ArcKit plugin:
# /plugin marketplace add tractorjuice/arc-kit

# For Gemini CLI, install the ArcKit extension:
# gemini extensions install https://github.com/tractorjuice/arckit-gemini

# For GitHub Copilot, check if prompt files exist
ls .github/prompts/arckit-*.prompt.md

# For OpenCode CLI, check if commands directory exists
ls .opencode/commands/

Template not found: Ensure you've run /arckit.principles first

# Check if templates exist
ls templates/

Project creation fails: Ensure you have an ArcKit repository initialized

# Initialize if needed
arckit init .

Support

Issues: GitHub Issues
Releases: GitHub Releases
Latest Version: v4.20.3

License

MIT License - see LICENSE for details

Acknowledgements

ArcKit is inspired by the methodology and patterns from Spec Kit, adapted for enterprise architecture governance workflows.

Built with ❤️ for enterprise architects who want systematic, AI-assisted governance.

dhairyagothi/100_days_100_web_project

This repository contains 100 web projects from basic to intermediate using html css and js Please star the repo before start working on it

🚀 100 Days 100 Web Projects

🌟 About This Project

Welcome to 100 Days 100 Web Projects! This is a comprehensive collection of 112+ web development projects ranging from beginner to intermediate level. Our goal is to help developers learn and practice web development through hands-on projects using various technologies.

🎯 What You'll Find Here:

Frontend Projects: HTML, CSS, JavaScript, React, Vue.js
Backend Projects: Node.js, Express.js, Flask, MERN Stack
Full-Stack Applications: Complete web applications with frontend and backend
Interactive Games: Browser-based games and entertainment apps
Utility Tools: Practical web tools and calculators
UI Components: Reusable components and design patterns

🔥 Featured Technologies:

🚀 Live Demo

🌐 Visit the Live Website: 100-days-100-web-project.vercel.app

The website features:

Interactive project showcase
Search functionality to find specific projects
Direct links to all project demos
Beautiful dark/light theme toggle
Responsive design for all devices

📚 All Projects (112 Total)

🎮 Interactive Demo Available!

🌐 Visit Live Website to see all projects with working demos!

Day	Project Name	Technologies	Type	Demo Link
1	To-Do List	HTML, CSS, JS	📝 Utility	View Demo
2	Digital Clock	HTML, CSS, JS	⏰ Widget	View Demo
3	Indian Flag	HTML, CSS	🎨 Animation	View Demo
4	Dropdown Nav Bar	HTML, CSS, JS	🧭 Navigation	View Demo
5	Animated Cursor	HTML, CSS, JS	✨ Effect	View Demo
6	Background Image Slider	HTML, CSS, JS	🖼️ Slider	View Demo
7	Typewriter Effect	HTML, CSS, JS	⌨️ Animation	View Demo
8	Parallel-X Website	HTML, CSS, JS	🌐 Website	View Demo
9	Captcha Generator	HTML, CSS, JS	🔐 Security	View Demo
10	QR Code Generator	HTML, CSS, JS	📱 Utility	View Demo
11	Express Server	Node.js, Express	🖥️ Backend	GitHub
12	Gmail Nodemailer	Node.js, Nodemailer	📧 Backend	GitHub
13	MERN Login Form	MongoDB, Express, React, Node	🔐 Full-Stack	GitHub
14	File Uploader	Node.js, Express	📁 Utility	GitHub
15	Progress Bar	HTML, CSS, JS	📊 UI Component	View Demo
16	Custom Scroll Bar	CSS	🎨 UI Component	View Demo
17	Swiper API Slider	HTML, CSS, JS	🖼️ Slider	View Demo
18	Carousel Solar System	HTML, CSS, JS	🪐 Animation	View Demo
19	Plant Website	HTML, CSS, JS	🌱 Website	View Demo
20	EveSparks	HTML, CSS, JS	✨ Website	View Demo
21	React Video Slider	React, Vite	🎥 React App	GitHub
22	Page Loader	HTML, CSS, JS	⏳ Animation	View Demo
23	Jarvis AI Assistant	HTML, CSS, JS	🤖 AI	View Demo
24	AI ChatBot	HTML, CSS, JS	💬 AI	View Demo
25	Tic-Tac-Toe	HTML, CSS, JS	🎮 Game	View Demo
26	Maze Game	HTML, CSS, JS	🎮 Game	View Demo
27	Memory Game	HTML, CSS, JS	🧠 Game	View Demo
28	Wordle Clone	HTML, CSS, JS	🎮 Game	View Demo
29	Snake Game	HTML, CSS, JS	🐍 Game	View Demo
30	Flappy Bird	HTML, CSS, JS	🐦 Game	View Demo
31	Password Manager	HTML, CSS, JS	🔐 Utility	View Demo
32	Missionaries & Cannibals	HTML, CSS, JS	🎮 Game	View Demo
33	Weather Forecasting	HTML, CSS, JS	🌤️ App	View Demo
34	Email Validator	HTML, CSS, JS	✅ Utility	View Demo
35	Vanilla JS Calculator	HTML, CSS, JS	🧮 Calculator	View Demo
36	Medical App	HTML, CSS, JS	🏥 App	View Demo
37	2048 Game	HTML, CSS, JS	🎮 Game	View Demo
38	GitHub Profile Finder	HTML, CSS, JS, API	👤 Utility	GitHub
39	Notes App	HTML, CSS, JS	📝 App	View Demo
40	Analog Clock	HTML, CSS, JS	⏰ Widget	View Demo
41	Scroll Dark Game	HTML, CSS, JS	🎮 Game	View Demo
42	Amazon Clone	HTML, CSS, JS	🛒 E-commerce	View Demo
43	Password Generator	HTML, CSS, JS	🔐 Utility	View Demo
44	BMI Calculator	HTML, CSS, JS	🧮 Calculator	View Demo
45	BlackJack Game	HTML, CSS, JS	🎰 Game	View Demo
46	Palindrome Generator	HTML, CSS, JS	📝 Utility	View Demo
47	Ping Pong Game	HTML, CSS, JS	🏓 Game	View Demo
48	Text to Voice Converter	HTML, CSS, JS	🔊 Utility	View Demo
49	URL Shortener	Node.js, Express	🔗 Backend	GitHub
50	Recipe Genie	React, Node.js	🍳 Full-Stack	GitHub
51	Netflix Clone	HTML, CSS, JS	🎬 Clone	View Demo
52	ClimaCode 2.0	HTML, CSS, JS	🌤️ App	View Demo
53	E-commerce Cart	HTML, CSS, JS	🛒 E-commerce	View Demo
54	Budget Tracker	HTML, CSS, JS	💰 Finance	View Demo
55	Cricket Game	HTML, CSS, JS	🏏 Game	View Demo
56	Pastebin Clone	Svelte	📝 App	GitHub
57	Glowing Social Icons	HTML, CSS	✨ UI Component	View Demo
58	Music App	HTML, CSS, JS	🎵 App	View Demo
59	Blog Page	HTML, CSS, JS	📝 Blog	View Demo
60	Marketing Website	HTML, CSS, JS	🌐 Website	View Demo
61	Hologram Button	HTML, CSS	✨ UI Component	View Demo
62	Solar System Explorer	HTML, CSS	🪐 Animation	View Demo
63	Image to Text App	HTML, CSS, JS	🖼️ OCR	View Demo
64	Zomato Clone	HTML, CSS, JS	🍕 Clone	View Demo
65	The Cube	HTML, CSS	🎲 3D Animation	View Demo
66	Flask Auth App	Python, Flask	🔐 Backend	GitHub
67	Blog Website	HTML, CSS, JS	📝 Blog	View Demo
68	3D Rotating Card	HTML, CSS	🎲 3D Animation	View Demo
69	Spotify Clone	HTML, CSS, JS	🎵 Clone	View Demo
70	Insect Catch Game	HTML, CSS, JS	🐛 Game	View Demo
71	Quotely Laughs	HTML, CSS, JS	😂 Entertainment	View Demo
72	Contact Book	Node.js, Express	📞 Backend	GitHub
73	Candy Crush Game	HTML, CSS, JS	🍭 Game	View Demo
74	Stock Profit Calculator	HTML, CSS, JS	📈 Finance	View Demo
75	Code Jump Space Game	HTML, CSS, JS	🚀 Game	View Demo
76	Animated Searchbar	HTML, CSS, JS	🔍 UI Component	View Demo
77	Rock Paper Scissors	HTML, CSS, JS	✂️ Game	View Demo
78	NPM Package Search	HTML, CSS, JS	📦 Utility	View Demo
79	LinkedIn Clone	HTML, CSS, JS	💼 Clone	View Demo
80	Resume Studio	HTML, CSS, JS	📄 Utility	View Demo
81	Simon Says Game	HTML, CSS, JS	🎮 Game	View Demo
82	Love Calculator	HTML, CSS, JS	💕 Fun	View Demo
83	Currency Exchange	HTML, CSS, JS	💱 Utility	View Demo
84	Lights Out Puzzle	HTML, CSS, JS	🎮 Game	View Demo
85	Image Search Engine	HTML, CSS, JS	🔍 Search	View Demo
86	3D Profile Card	HTML, CSS	🎲 3D Animation	View Demo
87	Breakout Game	HTML, CSS, JS	🎮 Game	View Demo
88	Job Dashboard	HTML, CSS, JS	💼 Dashboard	View Demo
89	N-Queen Solver	HTML, CSS, JS	👑 Algorithm	View Demo
90	Quiz App Timer	HTML, CSS, JS	❓ Quiz	View Demo
91	Voting App Backend	Node.js, Express	🗳️ Backend	GitHub
92	Slide Puzzle Game	HTML, CSS, JS	🧩 Game	View Demo
93	TextUtils	React	✏️ React App	View Demo
94	Hangman Game	HTML, CSS, JS	🎮 Game	View Demo
95	TodoList React TS	React, TypeScript, Tailwind	📝 React App	View Demo
96	HCL Color Generator	HTML, CSS, JS	🎨 Utility	View Demo
97	Time Capsule	HTML, CSS, JS	⏰ Utility	View Demo
98	Virtual Piano	HTML, CSS, JS	🎹 Music	View Demo
99	NASA APOD Extension	HTML, CSS, JS	🚀 Extension	View Demo
100	Text Saver Extension	HTML, CSS, JS	💾 Extension	View Demo
101	Finance Tracker	HTML, CSS, JS	💰 Finance	View Demo
102	Travel Booking Website	HTML, CSS, JS	✈️ Travel	View Demo
103	Drumkit Game	HTML, CSS, JS	🥁 Music	View Demo
104	Debug Website	HTML, CSS, JS	🐛 Development	View Demo
105	Periodic Table	HTML, CSS, JS	🧪 Educational	View Demo
106	Plants Website	HTML, CSS, JS	🌱 Website	View Demo
107	DocNow	HTML, CSS, JS	📄 Utility	View Demo
108	Expense Tracker	HTML, CSS, JS	💸 Finance	View Demo
109	Mood Tracker	HTML, CSS, JS	😊 Wellness	View Demo
110	CRYPTOSHOW	HTML, CSS, JS	💰 Crypto	View Demo
111	Whack-a-Mole Game	HTML, CSS, JS	🎮 Game	View Demo
112	Nykaa Clone	HTML, CSS, JS	💄 Clone	View Demo

📊 Project Categories:

🎮 Games: 25+ interactive games and puzzles
🧮 Calculators & Tools: 15+ utility applications
🌐 Websites & Clones: 20+ complete website replicas
📱 Apps: 15+ functional web applications
🎨 UI Components: 10+ reusable interface elements
🖥️ Backend Projects: 10+ server-side applications
⚛️ React Projects: 8+ modern React applications

Getting Started

🚀 Quick Start

🌐 View Projects Online

The easiest way to explore all projects is through our live website:

🔗 Visit: 100-days-100-web-project.vercel.app
✨ Features: Search projects, view demos, dark/light theme

💻 Local Development

Clone the repository:

# Using Git
git clone https://github.com/dhairyagothi/100_days_100_web_project.git

# Or use GitHub Desktop for GUI cloning

Navigate to project directory:
```
cd 100_days_100_web_project
```

Open the main website:

Simply open index.html in your browser
Or use a local server (recommended):

# Using Python
python -m http.server 8000

# Using Node.js
npx serve .

# Using VS Code Live Server extension

For individual projects:
- Navigate to public/[project-name]/
- Open the project's index.html file
- For Node.js projects, see individual README files

🧩 Project Structure

100_days_100_web_project/
├── index.html              # Main showcase website
├── index.js               # Main website functionality
├── style.css              # Main website styles
├── public/                # All individual projects
│   ├── TO_DO_LIST/       # Day 1: Todo List
│   ├── digital_clock/    # Day 2: Digital Clock
│   ├── snake_game/       # Day 29: Snake Game
│   └── ...               # 112+ projects
├── contributors/          # Contributors page
├── vercel.json           # Deployment configuration
└── README.md             # You are here!

🤝 Contributing

We welcome contributions from developers of all skill levels! Here's how you can contribute:

🆕 Adding New Projects

Fork the repository
Create a new branch: git checkout -b add-new-project
Add your project in the public/ directory
Update the project list in index.js
Test your project thoroughly
Submit a pull request

🐛 Bug Fixes & Improvements

Fork the repository
Create a new branch: git checkout -b fix-bug-name
Make your changes
Test thoroughly
Submit a pull request

📝 Documentation

Improve README files
Add project descriptions
Fix typos and formatting
Add setup instructions

📋 Contribution Guidelines

Follow existing code style and structure
Add appropriate comments to your code
Test your changes before submitting
Include a clear commit message
Update documentation if needed

📖 For detailed guidelines, see CONTRIBUTING.md

🎯 Learning Path

🌱 Beginner Projects (Days 1-30)

Perfect for those just starting with web development:

HTML/CSS fundamentals
Basic JavaScript interactions
Simple animations and effects

🚀 Intermediate Projects (Days 31-70)

For developers with some experience:

API integrations
Complex animations
Interactive games and applications

🔥 Advanced Projects (Days 71-112)

Challenging projects for experienced developers:

Full-stack applications
Complex algorithms
Modern frameworks (React, Node.js)

🛠️ Technologies Used

📞 Support & Community

🆘 Need Help?

💬 Discussions: GitHub Discussions
🐛 Bug Reports: Open an Issue
📧 Direct Contact: Create an issue for any questions

🌟 Stay Connected

📱 Instagram: @dhairyaa__31
💼 LinkedIn: Dhairya Gothi
🐙 GitHub: @dhairyagothi

📊 Repository Stats

⭐ Show Your Support

If this project helped you, please consider:

⭐ Starring this repository
🍴 Forking it to contribute
📢 Sharing it with others
💖 Following for more amazing projects

🏆 Contributors

Thanks to all these amazing people who have contributed to this project:

💖 Made with love by the open source community

🌟 Don't forget to star this repository if you found it helpful!

Chuyu-Team/Dism-Multi-language

Dism++ Multi-language Support & BUG Report

Dism-Multi-language

Dism++ resource files for supporting translation to various languages. The default language used for development is in Simplified Chinese.

[Data.xml]

Dism++ rules file which provides cleanup and optimization rules.

Languages of Dism++ (Languages folder)

Name	Language	Contributors
bg.xml	Bulgarian	Мартин Тайна, Pavel Belivakov
cs.xml	Czech	Richard Kahl
de.xml	German	franz@drwindows.de, Henry2o1o
en.xml	English	EMLVIRUS, Frag, Hexhu, raymai97, mdlgaofei, Mouri_Naruto, MikeGao, wondersnefu
es.xml	Spanish	Oleada, MS-PC2, nomemolesteis@gmail.com
fr.xml	French	JP.Sudret, P.Verdy
hu.xml	Hungarian	szuper
it.xml	Italian	Massimiliano F, Jumy
ja.xml	Japanese	山形まり花
ko.xml	Korean	OldMac, 阿泽西
pl-PL.xml	Polish	romuald68@gmail.com, Bladius (KuchtaPC2015@outlook.com)
pt.xml	Portuguese	JNylson
ru.xml	Russian	Black Alex, Vasiliy Nasonov, virus, Vladimir, ZT
tr.xml	Turkish	Kaya Zeren
zh-Hans.xml	Chinese Simplified	mingkuang
zh-Hant.xml	Chinese Traditional	GT Wang (http://mkvq.blogspot.com) 、jamesfuh、月下独酌

[chuyu-analysis]

Dism++崩溃统计后台。感谢 Reinforce-II。

[www.chuyu.me]

Base path for the official Dism++ website and help documentation. Dism++官方网站以及帮助文档。

Languages of Dism++ website (www.chuyu.me folder)

Name	Language	Contributors
de.xml	German	franz@drwindows.de
en.xml	English	Frag, Hexhu
es.xml	Spanish	MS-PC2
fr.xml	French	P.Verdy
ja.xml	Japanese	山形まり花
pt.xml	Portuguese	JNylson
ru.xml	Russian	AHOHNMYC
zh-Hans.xml	Chinese Simplified	mingkuang
zh-Hant.xml	Chinese Traditional	GT Wang (http://mkvq.blogspot.com)

alshedivat/al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

al-folio

A simple, clean, and responsive Jekyll theme for academics.

User community

The vibrant community of al-folio users is growing! Academics around the world use this theme for their homepages, blogs, lab pages, as well as webpages for courses, workshops, conferences, meetups, and more. Check out the community webpages below. Feel free to add your own page(s) by sending a PR.

Academics	★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
Labs	★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★ ★
Courses	CMU PGM (S-19) CMU DeepRL (S-21, F-21, S-22, F-22, S-23, F-23) CMU MMML (F-20, F-22) CMU AMMML (S-22, S-23) CMU ASI (S-23) CMU Distributed Systems (S-24)
Conferences & workshops	ICLR Blog Post Track (2023, 2024) ML Retrospectives (NeurIPS: 2019, 2020; ICML: 2020) HAMLETS (NeurIPS: 2020) ICBINB (NeurIPS: 2020, 2021) Neural Compression (ICLR: 2021) Score Based Methods (NeurIPS: 2022) Images2Symbols (CogSci: 2022) Medical Robotics Junior Faculty Forum (ISMR: 2023) Beyond Vision: Physics meets AI (ICIAP: 2023) Workshop on Diffusion Models (NeurIPS: 2023) Workshop on Structured Probabilistic Inference & Generative Modeling (ICML: 2023, 2024) Workshop on Foundation and Generative Models in Biometrics (ICCV 2025, CVPR 2026)

Lighthouse PageSpeed Insights

Desktop

Run the test yourself: Google Lighthouse PageSpeed Insights

Mobile

Run the test yourself: Google Lighthouse PageSpeed Insights

al-folio

Getting started

⚠️ Important: Use "Use this template" (not fork)

When creating your own website with al-folio, you have two options:

✅ Recommended: Click "Use this template" – This creates a clean copy that is independent from the main al-folio repository. Changes you make to your site won't be accidentally submitted to al-folio as pull requests.
❌ Not recommended: Forking the repository – This keeps a link to the main al-folio repo, making it easy to accidentally submit your personal site changes as contributions to our project.

If you already forked: Don't worry! You can still work with your fork normally. Just make sure to:

Make changes on a dedicated branch (e.g., my-site-updates)
When pushing changes, always verify you're pushing to your own repository, not the main al-folio repository
Never create pull requests to alshedivat/al-folio unless you're intentionally contributing improvements that benefit all users

For quick setup, see QUICKSTART.md.

Want to learn more about Jekyll? Check out this tutorial. Why Jekyll? Read Andrej Karpathy's blog post! Why write a blog? Read Rachel Thomas blog post.

Installing and Deploying

For installation and deployment details please refer to INSTALL.md.

Customizing

For customization details please refer to CUSTOMIZE.md.

GitHub Copilot Agents

This repository includes two specialized GitHub Copilot agents to enhance your development experience:

Customization Agent

The Customization Agent helps you personalize your al-folio website by:

Guiding you through configuration changes step-by-step
Modifying files directly in your repository
Explaining technical concepts in plain language (great for users without coding experience)
Assisting with common tasks like updating your CV, adding publications, creating blog posts, and customizing themes

See CUSTOMIZE.md § GitHub Copilot Customization Agent for detailed usage instructions.

Documentation Agent

The Documentation Agent maintains clear and up-to-date project documentation by:

Updating documentation files when features change
Writing in a style accessible to academics and researchers
Keeping documentation synchronized with the codebase
Following documentation best practices

See CONTRIBUTING.md § GitHub Copilot Agents for more information.

Requirements: Both agents require a GitHub Copilot subscription. For more information about GitHub Copilot and how to use agents, see the GitHub Copilot documentation.

Documentation

Comprehensive guides for all aspects of your al-folio website:

Quick Start – Get running in 5 minutes
Installation & Deployment – Set up your site on GitHub Pages or other platforms
Customization Guide – Personalize your website (CVs, publications, themes, etc.)
Troubleshooting – Fix common issues (deployment, build, styling, content)
FAQ – Frequently asked questions and solutions
Analytics – Add website analytics and visitor tracking
SEO Guide – Optimize for search engines and improve discoverability

Features

Light/Dark Mode

This template has a built-in light/dark mode. It detects the user preferred color scheme and automatically switches to it. You can also manually switch between light and dark mode by clicking on the sun/moon icon in the top right corner of the page.

CV

Your CV can be generated in one of two modern formats: RenderCV (recommended, with automatic PDF generation) or JSONResume (standardized JSON format). You can use both simultaneously and switch between them, or maintain just the one you prefer.

For setup and customization details, see Modifying the CV information in CUSTOMIZE.md.

People

You can create a people page if you want to feature more than one person. Each person can have its own short bio, profile picture, and you can also set if every person will appear at the same or opposite sides.

Publications

Your publications page is generated automatically from your BibTeX bibliography. You can customize publication display, add extra information like PDFs, and control sorting behavior.

For setup, BibTeX field documentation, and customization options, see Adding a new publication and Managing publication display in CUSTOMIZE.md.

Collections

This Jekyll theme implements collections to organize content into categories. The theme comes with default collections for news, projects, books, and teachings. You can easily create your own collections for apps, stories, courses, or any other creative work.

For detailed instructions on creating and customizing collections, see Adding Collections in CUSTOMIZE.md.

Layouts

al-folio comes with stylish layouts for pages and blog posts.

The iconic style of Distill

The theme allows you to create blog posts in the distill.pub style:

For more details on how to create distill-styled posts using <d-*> tags, please refer to the example.

Full support for math & code

al-folio supports fast math typesetting through MathJax and code syntax highlighting using GitHub style. Also supports chartjs charts, mermaid diagrams, and TikZ figures.

Photos, Audio, Video and more

Photo formatting is made simple using Bootstrap's grid system. Easily create beautiful grids within your blog posts and project pages, also with support for video and audio embeds:

Other features

GitHub's repositories and user stats

al-folio displays GitHub repositories and user stats on the /repositories/ page using github-readme-stats and github-profile-trophy.

To configure which repositories and GitHub profiles to display, see Modifying the user and repository information in CUSTOMIZE.md.

Theming

al-folio offers a variety of beautiful theme colors to choose from. The default is purple, but you can customize colors, fonts, spacing, and more to match your style.

For detailed customization instructions, see Changing theme color and Customizing fonts, spacing, and more in CUSTOMIZE.md.

Social media previews

al-folio supports Open Graph preview images on social media. When enabled, your site's pages display rich preview objects with images, titles, and descriptions when shared.

For setup and customization, see Social media previews in CUSTOMIZE.md.

Atom (RSS-like) Feed

It generates an Atom (RSS-like) feed of your posts, useful for Atom and RSS readers. The feed is reachable simply by typing after your homepage /feed.xml. E.g. assuming your website mountpoint is the main folder, you can type yourusername.github.io/feed.xml

By default, blog posts display related posts at the bottom. These are selected by finding the most recent posts that share tags with the current post. You can customize this behavior on a per-post or site-wide basis.

For configuration details, see Related posts in CUSTOMIZE.md.

Code quality checks

Currently, we run some checks to ensure that the code quality and generated site are good. The checks are done using GitHub Actions and the following tools:

Prettier - check if the formatting of the code follows the style guide
lychee - check for broken links
Axe (need to run manually) - do some accessibility testing

We decided to keep Axe runs manual because fixing the issues are not straightforward and might be hard for people without web development knowledge.

GDPR Cookie Consent Dialog

al-folio includes a built-in, GDPR-compliant cookie consent dialog to ensure your website respects visitor privacy. The dialog is powered by Vanilla Cookie Consent and integrates seamlessly with all supported analytics providers.

When enabled, analytics scripts are blocked until the user explicitly consents, and user preferences are saved across visits. This is essential for websites serving visitors in the European Union and other regions with strict privacy regulations.

For complete setup and customization details, see GDPR Cookie Consent Dialog in CUSTOMIZE.md.

FAQ

For frequently asked questions, please refer to FAQ.md.

Contributing

Contributions to al-folio are very welcome! Before you get started, please take a look at the guidelines.

If you would like to improve documentation or fix a minor inconsistency or bug, please feel free to send a PR directly to main. For more complex issues/bugs or feature requests, please open an issue using the appropriate template.

Maintainers

Our most active contributors are welcome to join the maintainers team. If you are interested, please reach out!

_Maruan

_{Rohan Deb Sarkar}

_{Amir Pourmand}

_George

All Contributors

Star History

License

The theme is available as open source under the terms of the MIT License.

Originally, al-folio was based on the *folio theme (published by Lia Bogoev and under the MIT license). Since then, it got a full re-write of the styles and many additional cool features.

vernesong/OpenClash

A Clash Client For OpenWrt

OpenClash

本插件是一个可运行在 OpenWrt 上的 Mihomo(Clash) 客户端

兼容 Shadowsocks、ShadowsocksR、Vmess、Trojan、Snell 等协议，根据灵活的规则配置实现策略代理

使用手册

Wiki

下载地址

IPK & APK 前往下载

依赖

luci
luci-base
dnsmasq-full
bash
curl
ca-bundle
ipset
ip-full
ruby
ruby-yaml
unzip
iptables(iptables)
kmod-ipt-nat(iptables)
iptables-mod-tproxy(iptables)
iptables-mod-extra(iptables)
kmod-tun(TUN模式)
luci-compat(Luci >= 19.07)
ip6tables-mod-nat(iptables-ipv6)
kmod-inet-diag(PROCESS-NAME)
kmod-nft-tproxy(Firewall4)

编译

从 OpenWrt 的 SDK 编译

# 解压下载好的 SDK
curl -SLk --connect-timeout 30 --retry 2 "https://archive.openwrt.org/chaos_calmer/15.05.1/ar71xx/generic/OpenWrt-SDK-15.05.1-ar71xx-generic_gcc-4.8-linaro_uClibc-0.9.33.2.Linux-x86_64.tar.bz2" -o "/tmp/SDK.tar.bz2"
cd \tmp
tar xjf SDK.tar.bz2
cd OpenWrt-SDK-15.05.1-*

# Clone 项目
mkdir package/luci-app-openclash
cd package/luci-app-openclash
git init
git remote add -f origin https://github.com/vernesong/OpenClash.git
git config core.sparsecheckout true
echo "luci-app-openclash" >> .git/info/sparse-checkout
git pull --depth 1 origin master
git branch --set-upstream-to=origin/master master

# 编译 po2lmo (如果有po2lmo可跳过)
pushd luci-app-openclash/tools/po2lmo
make && sudo make install
popd

# 开始编译

# 先回退到SDK主目录
cd ../..
make package/luci-app-openclash/luci-app-openclash/compile V=99

# IPK文件位置
./bin/ar71xx/packages/base/luci-app-openclash_*-beta_all.ipk

# 同步源码
cd package/luci-app-openclash/luci-app-openclash
git pull

# 您也可以直接拷贝 `luci-app-openclash` 文件夹至其他 `OpenWrt` 项目的 `Package` 目录下随固件编译

make menuconfig
# 选择要编译的包 LuCI -> Applications -> luci-app-openclash

许可

MIT License
内核 Mihomo by MetaCubeX
本项目代码基于 Luci For Clash by frainzy1477
IP检查 IP by SukkaW
控制面板 zashboard by Zephyruso
控制面板 yacd by haishanh
流媒体解锁检测 RegionRestrictionCheck by lmc999

请作者喝杯咖啡

PayPal

USDT-TRC20

DigitalPlatDev/FreeDomain

DigitalPlat FreeDomain: Free Domain For Everyone

🌐 Welcome to DigitalPlat Domain

Welcome to DigitalPlat FreeDomain, where we believe everyone deserves a digital identity. Whether you're an individual, or an organization, we’re offering free domain names to bring your ideas to life – no strings attached!

With FreeDomain, you’re free to register a unique domain and host it with your favorite DNS provider, like Cloudflare, FreeDNS by Afraid.org, or Hostry. Get online with complete freedom, and keep your wallet happy.

✔️ Why Free Domains?

At DigitalPlat FreeDomain, we’re on a mission to make the web more accessible. We believe that the cost of a domain shouldn’t hold anyone back from creating a website. Our goal is to make the internet an open space where everyone can have their own place online, regardless of budget.

DigitalPlat FreeDomain is independently designed and maintained by Edward Hsing, founder of the DigitalPlat Foundation.

🌍 Available Domain Extensions

.DPDNS.ORG
.US.KG
.QZZ.IO
.XX.KG
.QD.JE

(More extensions coming soon!)

🌍 Ready to Claim Your Free Domain?

Jump in and register your domain by visiting our site:

➡️ DigitalPlat FreeDomain Dashboard

📝 Read our tutorial

🌟 Trusted by Thousands

With over 500,000 domains already registered, DigitalPlat FreeDomain is a trusted choice for individuals and organizations alike. Join our growing community and claim your own free domain today!

❔ FAQ

Check FAQ Page

🤝 Join Our Community!

🆕 Join our official DigitalPlat FreeDomain Discord server today! Be the first to know about the latest updates, get support, and connect with the community. Got questions? Facing challenges? Or just want to share what you're building? Come hang out with us 🚀

⚠️ Security Notice Our previous Telegram account and group were compromised and are no longer under our control. Please do not trust any messages, links, or announcements from Telegram, especially anything related to bonuses, earnings, or external sites. We are no longer using Telegram as an official communication channel.

⏭️ What's next

We might introduce more domain options and free hosting in the future to help as many people as possible!

We can’t wait to see what you build!

🚨 Abuse Reporting

We take domain name abuse seriously and are committed to maintaining a safer and more open internet. Every report is carefully reviewed, and response times may vary from a few hours to several days, depending on the complexity of the case.

Email: abusereport@digitalplat.org

🧠 Story

This started as a small DNS experiment when I was 15, letting a few friends use subdomains.

Over time, it grew into something people actually rely on, and running it turned out to be much harder than building it.

I wrote a bit about how it evolved here:
https://dev.to/edwardhsing/i-bought-a-domain-at-15-now-it-powers-400000-users-7ol

CoolDude2349/Offline-HTML-Games-Pack

300 offline HTML games, each on a single file

A collection of offline HTML games.

A repo filled with 300 offline games that can each run on a single file. This is a good option if you are having internet connectivity issues, or you're at some place with restricted internet.

Usage: Under the Code button, select Download ZIP. It may take a while to download. After, extract the zip by right clicking on it and selecting Extract All. Now you have the repo containing the games all in a folder. You can also clone the repository using git.

The downside of inlining everything is the file size. If you're running the files via an online code editor, it may be better to use the single-file html. You can either get the files from the web or import your own.

tabler/tabler

Tabler is free and open-source HTML Dashboard UI Kit built on Bootstrap

A premium and open source dashboard template with a responsive and high-quality UI.

Testing

Browser testing via:

🔎 Preview

Tabler is fully responsive and compatible with all modern browsers. Thanks to its modern and user-friendly design you can create a fully functional interface that users will love! Choose the layouts and components you need and customize them to make your design consistent and eye-catching. Every component has been created with attention to detail to make your interface beautiful! Show me a demo

🚀 Features

We've created this admin panel for everyone who wants to create templates based on our pre-made components. Our mission is to deliver a user-friendly, clear and easy administration panel that can be used by both simple websites and sophisticated systems. The only requirement is basic HTML and CSS (and some Liquid) knowledge — as a reward, you'll be able to manage and visualize different types of data in the easiest possible way!

Responsive: With the support for mobile, tablet and desktop displays, it doesn’t matter what device you’re using. Tabler is responsive in all major browsers.
Cross Browser: Our theme works perfectly with the latest Chrome, Firefox+, Safari, Opera, Edge and mobile browsers. We work hard to provide continuous support for them.
HTML5 & CSS3: We use only modern web technologies, such as HTML5 and CSS3. Our theme includes some subtle CSS3 animations, which will help you attract attention.
Clean Code: We followed Bootstrap’s guidelines carefully to make your integration as easy as possible. All code is handwritten and W3C valid.
Demo pages: Tabler features over 20 individual pages using various components, which gives you the freedom to choose and combine. All components can vary in color and styling that you can easily modify using Sass. Sky is the limit!

📖 Documentation

The documentation is available at https://docs.tabler.io/

🪴 Project Activity

Installation

Package Managers

Tabler is distributed via npm. You can install it with this or your preferred JavaScript package manager:

npm install --save @tabler/core

CDN support

All files included in @tabler/core npm package are also available over a CDN.

Javascript

<script src="https://cdn.jsdelivr.net/npm/@tabler/core@latest/dist/js/tabler.min.js"></script>

Styles

<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@tabler/core@latest/dist/css/tabler.min.css">

Building locally

To build a copy of Tabler locally, you have two options. You can either set up your device directly with the development tools required to build Tabler, or if you would prefer not to install all the development dependencies directly onto your device, you can use a Dockerfile that Tabler provides to build a docker image. Instructions follow below.

First steps: Downloading the Tabler source files

With either method, the first thing you'll want to do is download a copy of the Tabler source files to your device.

From the Tabler GitHub releases page

If you don't want to edit the source code once you've downloaded it, and aren't interested in merging future project updates into your copy, you can just download the source files straight from the Tabler releases on GitHub and extract the contents to a directory called tabler.

Cloning with Git

If you do wish to edit the source code after downloading it, for example to contribute changes back to the Tabler project, you'll want to do this by cloning it with Git:

If you don't have Git installed on your device, download and install it. You can find instructions at https://git-scm.com/downloads.
(Optional) Windows users: you could optionally install Git in the C:\Program Files\git\bin directory and run npm config set script-shell "C:\\Program Files\\git\\bin\\bash.exe" to change the default shell.
Clone the Tabler project into a folder on your device. Instructions can be found at cloning a repository.

Installing and running development tools directly

Install Node.js, which we use to manage our dependencies.
Install pnpm (We recommend either by Using Corepack or by Using npm)
From the root /tabler directory where you downloaded the Tabler source files, run installation on the command line:

pnpm install

Then execute the following to start up the application stack:

pnpm run start

Open http://localhost:3000 to view the preview website in your browser, or http://localhost:3010 to view the documentation website - and voilà. Changes to most of the source files of Tabler core, preview and docs will rebuild the application and refresh the page.

Note: If you wish to perform a one-off build without auto-refresh on any changes, you can run:

pnpm run build

You can open http://localhost:3001 to configure the Web server.

Installing and running development tools with Docker

Plain Docker

Here is an example of how to use this image:

From the root /tabler directory where you downloaded the Tabler source files, build the tabler image:

docker build -t tabler .

Run the tabler image. The following command mounts the src directory into the container, exposes port 3000 to browse the website locally, and exposes port 3001 to automatically sync changes:

docker run -p 3000:3000 -p 3001:3001 -v $(pwd)/src:/app/src tabler

Open your browser to http://localhost:3000. Edit anything in the src/ folder and watch your browser refresh the page after it has been rebuilt.

Docker Compose

You can also use the docker compose config from this repo. From the root /tabler directory where you downloaded the Tabler source files, use docker compose build && docker compose up or docker compose up --build to build and start the container. Edit anything in the src/ folder the same way as with plain docker and access the same URLs and ports in your browser.

Bugs and feature requests

Found a bug or have a feature request? Please open a new issue.

🤓 Creators

Paweł Kuna

Bartłomiej Gawęda

👨‍🚀 Contributors

This project exists thanks to all the people who contribute.

Social media

Stay up to date by joining our community on X and Facebook

License

See the LICENSE file.

microsoft/dotnet

This repo is the official home of .NET on GitHub. It's a great starting point to find many .NET OSS projects from Microsoft and the community, including many that are part of the .NET Foundation.

.NET Home

This repository is a starting point to learn about and engage in .NET and .NET open source projects.

This repository is not an official .NET or .NET Framework support location, however, we will respond to issues filed here as best we can. Please file .NET product issues at main project repos below.

In this repository

Please contribute to this repository via pull requests

Finding .NET Open Source Projects

Here are some excellent community-maintained lists of projects & libraries:

There are many projects that you can use and contribute to, some of which are listed below. Please do contribute to these projects!

.NET

.NET Docs

.NET Framework

Xamarin

Community

Here is a short list of projects to check out:

There are additional templates available for dotnet new. For more information, see Available templates for dotnet new

.NET Foundation

Many .NET open source projects are part of the .NET Foundation. Microsoft has contributed many projects, including ASP.NET Core and .NET Core. You may want to consider joining the .NET Foundation.

Check out the .NET Foundation Discord Server to see what others are talking about, or start a new discussion to ask a question or make a point.

License

This repository is licensed with the MIT license.

gustavoguanabara/html-css

Curso de HTML5 e CSS3

Material público para o ensino básico de HTML5 e CSS3 para alunos iniciantes. Acesse o material em PDF, analise o código disponibilizado para cada exercício e veja-os funcionando em execução direta via repositório GitHub.

Direitos de uso

Você tem todo o direito de usar esse material para seu próprio aprendizado. Professores também podem ter acesso a todo o conteúdo e usá-los com seus alunos. Porém todos o que usarem esse material - seja para qual for a finalidade - deverão manter a referência ao material original, criado e disponibilizado pelo Prof. Gustavo Guanabara. Este conteúdo não poderá ser utilizado em nenhuma hipótese para ser replicada - integral ou parcialmente - por autores/ editoras/ instituições de ensino para criar livros ou apostilas, com finalidades de obter ganho financeiro com ele.

GitHub HTML Daily Trending

CyberAlbSecOP/Awesome_GPT_Super_Prompting

What will you find in V.2.0:

Legend:

Jailbreak Hall Of Fame:

🚨 Jailbreaks

🕵️‍♂️ GPT Agents System Prompt Leaks

🛡️ Prompt Injection

🔐 Secure Prompting

🗂️ GPTs Lists

📚 Prompts Libraries

🛠️ Prompt Engineering

🔎 Prompt Sources

⚙️ Ai Automation Tools

🧠 Cyber-Albsecop GPT Agents

To do for V3.00

Star History

Keywords:

trycua/cua

Choose Your Path

Cua Driver - Background computer-use on macOS

Cua - Agent-Ready Sandboxes for Any OS

CuaBot - Co-op computer-use for any agent

Cua-Bench - Benchmarks & RL Environments

Lume - macOS Virtualization

Packages

Resources

Contributing

License

Trademarks

wilsonfreitas/awesome-quant

Awesome Quant

Contents

Numerical Libraries & Data Structures

Financial Instruments & Pricing

Technical Indicators

Trading & Backtesting

Portfolio Optimization & Risk Analysis

Factor Analysis

Sentiment Analysis & Alternative Data

Time Series Analysis

Market Data & Data Sources

Prediction Markets

Calendars & Market Hours

Visualization

Excel & Spreadsheet Integration

Quant Research Environments

Cross-Language Frameworks

Reproducing Works, Training & Books

Commercial & Proprietary Services

Related Lists

tractorjuice/arc-kit

ArcKit - Enterprise Architecture Governance Toolkit

📖 The ArcKit Book

Star History

Quick Start

Installation

Platform Support

Initialize a Project

Start Using ArcKit

Upgrading

Explore Example Outputs

Why ArcKit?

Problem: Architecture Governance is Broken

Solution: Structured, AI-Assisted Governance

UK Government Compliance

EU, French & Austrian Regulatory Compliance (Community)

Canada Federal Overlay (12 commands)

UAE Federal Overlay (Community-contributed)

The ArcKit Workflow

Phase 0: Project Planning

Phase 1: Establish Governance

Phase 2: Stakeholder Analysis

Phase 3: Risk Assessment

Phase 4: Business Case Justification

Phase 5: Define Requirements

Phase 5.3: Platform Strategy Design (Optional - for Multi-Sided Platforms)

Phase 5.5: Data Modeling

Phase 5.7: Data Protection Impact Assessment

Phase 5.8: Data Source Discovery