Show HN: Algo-Trading-Skills – trading failure modes AI agents don't know

A community project called Algo-Trading-Skills has released 501 structured algorithmic trading skills across 16 engineering domains, each backed by working reference implementations and 20,291 unit tests, under the Apache 2.0 license. The library follows the agentskills.io standard and works with Claude Code, GitHub Copilot, Codex CLI, Cursor, and Gemini CLI, mapping skills to frameworks including SEC Rule 15c3-5, Reg NMS, Reg SHO, FINRA, EU MiFID II/RTS 6/MAR, UK FCA, ASIC, SEBI, and ISDA OTC standards. The project is independent and not affiliated with Anthropic PBC, and its authors state it provides engineering guidance rather than financial, legal, or compliance advice.

501 algorithmic trading skills · 16 engineering domains · 5 regulatory & exchange frameworks · 501 working reference implementations backed by 20,291 unit tests · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI and any tool that reads SKILL.md · Apache 2.0 Get Started quick-start · What's Inside whats-inside--16-categories · How It's Verified what-verified-means-here · Frameworks & Standards five-regulatory--exchange-frameworks-one-skill-library · Platforms compatible-platforms--zero-config-auto-discovery · Contributing contributing Community Project — This is an independent, community-created project. Not affiliated with Anthropic PBC or any broker, exchange, or vendor referenced in this repository. ⚠️ 📈 Engineering Guidance, Not Financial, Legal, or Compliance Advice — Authorized & lawful use only. These skills encode production engineering practices for trading infrastructure. They do not constitute financial, legal, tax, or regulatory compliance advice, do not guarantee strategy profitability, and do not eliminate the risk of capital loss in live trading. Only deploy against paper accounts or live environments where risk limits are strictly enforced. Consult qualified legal, tax, and compliance professionals in your jurisdiction before deploying live trading systems. See SECURITY.md /HimanshuJ16/Algo-Trading-Skills/blob/main/SECURITY.md and CODE OF CONDUCT.md /HimanshuJ16/Algo-Trading-Skills/blob/main/CODE OF CONDUCT.md . An AI coding agent can write a WebSocket client, a backtest loop, or an order-placement function that looks completely correct — right library calls, clean structure, plausible logic — and still fail catastrophically in production for reasons that have nothing to do with code syntax: a broker invalidates a token overnight in a way its docs don't mention, a backtest silently uses a bar's own close to predict its own direction, a risk limit lives inside the same function it's supposed to constrain, or a WebSocket callback blocks the read loop during exactly the volatility spike a strategy exists to catch. Your AI agent doesn't know these failure modes — unless you give it these skills. This repo contains 501 structured skills spanning 16 engineering domains , each following the agentskills.io https://agentskills.io open standard. The library maps across key financial regulatory & exchange frameworks — SEC Rule 15c3-5, Reg NMS / Reg SHO, FINRA, EU MiFID II / RTS 6 / MAR, UK FCA, ASIC, SEBI, and ISDA OTC derivative standards. Clone it, point your agent at it, and your next trading system deployment gets expert-level quant infrastructure guidance in seconds. Every skill also states where it stops . A When NOT to Use section on all 501 skills names the cases the skill does not cover and hands each one to the skill that does — because an agent applying a correct playbook to the wrong problem is its own failure mode, and it is the one a keyword match is most likely to cause. Each skill maps to the industry standards, exchange protocols, and regulatory mandates that fit its subject: | Framework / Standard | Scope | What It Maps | Key Mapped Skills | |---|---|---|---| | US SEC / FINRA | SEC Rule 15c3-5, Reg NMS Rule 611, Reg SHO, PDT Rule 4210, Form 1099-B | Pre-trade risk controls, order protection, short sale locates, pattern day trading, tax lot reconciliation | us-reg-nms-order-protection-rule-compliance , us-reg-sho-short-sale-locate-requirements , sec-rule-15c3-5-risk-controls-us , wash-sale-rule-tracking-us | | EU MiFID II / RTS 6 / MAR | MiFID II Article 48, RTS 6 organizational requirements, MAR market abuse surveillance | System resilience, kill switches, OTR limits, wash trade & spoofing self-detection, double volume caps | mifid-ii-algo-trading-compliance-eu , wash-trade-and-spoofing-self-detection , eu-market-abuse-regulation-mar-surveillance | | UK FCA & Senior Managers Regime | FCA SYSC 25, MIFIDPRU, Senior Managers & Certification Regime SM&CR | Algorithmic trading system controls, algorithmic accountability, key person governance | uk-fca-algorithmic-trading-systems-controls , uk-senior-managers-regime-algo-accountability | | Global Regulatory ASIC, SEBI, MAS, IIROC | ASIC MIR, SEBI Algo Circulars, MAS Cyber Hygiene, IIROC Electronic Trading | Regional exchange order tagging, circuit breakers, risk-gate dependencies, kill switches | asic-market-integrity-rules-automated-trading , india-sebi-algo-trading-tagging-requirements , mas-singapore-algo-trading-guidelines | | ISDA & OTC Derivatives | ISDA Master Agreement, SPAN Margin, Options Greeks, Variance Swaps | Collateral management, cross-margining, delta hedging, synthetic TRS exposure, volatility derivatives | options-margin-span-calculation-global , total-return-swap-synthetic-exposure , variance-swap-and-volatility-derivative-pricing | Example — Each skill maps directly to regulatory mandates, broker APIs, and institutional standards: | Skill | Primary Regulatory / Exchange Standard | Broker / Platform Touchpoints | Operational Safety Target | |---|---|---|---| | order-placement-idempotency /HimanshuJ16/Algo-Trading-Skills/blob/main/skills/order-placement-idempotency | SEC Rule 15c3-5 / MiFID II RTS 6 | Fyers, Zerodha, Breeze, Upstox, Alpaca, IBKR | Zero duplicate executions on reconnection | | kill-switch-and-drawdown-circuit-breakers /HimanshuJ16/Algo-Trading-Skills/blob/main/skills/kill-switch-and-drawdown-circuit-breakers | SEC Rule 15c3-5 Pre-Trade Controls | Universal / Broker-Agnostic | Instant capital protection on drawdown breach | | wash-trade-and-spoofing-self-detection /HimanshuJ16/Algo-Trading-Skills/blob/main/skills/wash-trade-and-spoofing-self-detection | EU MAR / FINRA Rule 5210 | Exchange Order Feeds | Pre-trade self-cross prevention & cancellation audit | | us-reg-sho-short-sale-locate-requirements /HimanshuJ16/Algo-Trading-Skills/blob/main/skills/us-reg-sho-short-sale-locate-requirements | US SEC Reg SHO Rule 203 b 1 | US Equity Brokers / Prime Brokers | Mandatory pre-short locate verification & buy-in tracking | | withdrawal-velocity-limits-and-anomaly-detection /HimanshuJ16/Algo-Trading-Skills/blob/main/skills/withdrawal-velocity-limits-and-anomaly-detection | MAS Cyber Hygiene / Custody Risk | Coinbase, Fireblocks, BitGo, HSM | Automated hot wallet freeze on velocity breach | Option 1: Claude Code — install one domain, not the whole library /plugin marketplace add HimanshuJ16/Algo-Trading-Skills /plugin install algo-trading-risk-management /plugin install algo-trading-broker-integration Option 2: skills CLI — pick the skills you want interactively npx skills add HimanshuJ16/Algo-Trading-Skills Option 3: git clone, then run the gates yourself git clone https://github.com/HimanshuJ16/Algo-Trading-Skills.git cd Algo-Trading-Skills pip install -r requirements-dev.txt python tools/validate skills.py structure, frontmatter, cross-references & packaging python tools/run all tests.py every skill's unit test suite, isolated per subprocess Install one domain, not all of them. Claude Code loads the name and description of every skill in an installed plugin into the model's context at the start of every session. The marketplace therefore ships one plugin per engineering domain algo-trading-risk-management , algo-trading-execution-algorithms , … , each a few thousand tokens. An algo-trading-skills-all plugin exists for completeness, but it costs tens of thousands of tokens per session — reach for it only if you know you want that. One caveat on disk rather than context: every plugin entry points at the repository root, so installing a single domain checks out the whole tree about 100 MB ; only that domain's skills are loaded into the session. Run one skill's suite on its own — the same command every skill quotes in its own Verification section: python -m unittest discover -s skills/order-placement-idempotency/scripts Works immediately with Claude Code, GitHub Copilot, OpenAI Codex CLI, Cursor, Gemini CLI, and any agentskills.io-compatible platform. The quantitative trading and financial software engineering domain requires deep practitioner knowledge across market microstructure, exchange protocols, and risk engineering. AI agents can help build and scale trading infrastructure — but only if they have structured practitioner playbooks to work from. Today's generic LLMs can write Python code and API wrappers, but they lack the operational context that separates code which works in a notebook from code that survives a live market. Existing trading libraries give you broker SDKs, indicator formulas, or naive strategy backtests. None of them give an AI agent the structured decision-making workflow a senior quant infrastructure engineer follows: when to use each technique, when not to, what prerequisites to check, how to execute step-by-step, and how to verify results in production. That is the gap this project fills. Algo-Trading-Skills is not a collection of toy scripts. It is an AI-native knowledge base built from the ground up for the agentskills.io https://agentskills.io standard — YAML frontmatter for sub-second discovery, structured Markdown for step-by-step execution, and reference files for deep technical context. Every skill encodes real practitioner workflows, not generic LLM summaries. Skill libraries are easy to generate and hard to trust. Everything in this table is re-checked by CI on every push and pull request, on Python 3.10, 3.12 and 3.13, so the claims stay true or the build goes red. | 501 working reference implementations | ~292,000 lines of Python under skills/ /scripts/ . Not pseudocode — importable modules that validate their inputs and raise on bad data; about half define their own exception classes, the rest raise the builtins. 466 of the 501 import nothing outside the Python standard library; the 35 that do reach mostly for numpy or pandas, so the whole suite still runs on requirements-dev.txt alone. | | 501 unit test suites · 20,291 tests | ~228,000 lines of tests. Each suite runs in its own subprocess with a timeout, so no skill can leak module state into another or hang the build. A skill whose own reference implementation fails its own tests fails the build. | | A machine-enforced contract | tools/validate skills.py /HimanshuJ16/Algo-Trading-Skills/blob/main/tools/validate skills.py checks the frontmatter contract, the seven required body sections, scripts/ layout, every skill cross-reference in both skills and repo docs, that every documented test command runs from the repository root, and that the plugin manifests cover every skill exactly once. | | The specification, not our reading of it | CI also runs skills-ref https://github.com/agentskills/agentskills/tree/main/skills-ref , the official agentskills.io reference validator, against every skill. It needs Python 3.11+, so that job runs on the newer interpreters while the library itself stays 3.10-compatible. | | Descriptions that say when to trigger | Every description starts with "Use when …" and fits in 280 characters — enforced, because it is the only thing an agent reads before choosing a skill, and it costs context on every session. | | Generated files can't drift | index.json and the plugin marketplace are generated and carry no timestamp; --check modes fail CI if either is stale. | | Verification you can paste | Every skill quotes a runnable command in its Verification section, alongside the concrete assertions to check by hand. | | Sourced, or explicitly unsourced | 458 of 501 references/standards.md cite at least one primary source — the rule text, the exchange notice, the vendor spec. Where no external standard exists, the file says so and labels its numbers as configurable defaults rather than inventing an authority for them. | | Stated scope boundaries | When NOT to Use on every skill, naming the excluded cases and handing each to the skill that owns it. | | Examples that use the real code | The three walkthroughs in examples/ import the actual skill helpers rather than re-implementing them, and CI runs all three. | The CI workflow is .github/workflows/validate-skills.yml /HimanshuJ16/Algo-Trading-Skills/blob/main/.github/workflows/validate-skills.yml . The library covers 16 core engineering domains spanning domestic and global markets — crypto exchanges, forex brokers, multi-currency and multi-timezone data handling, regulatory compliance, multi-asset derivatives, execution algorithms, custody/security, cross-strategy portfolio management, market microstructure, alternative-data research, and tax/accounting. | Domain | Skills | Key capabilities | |---|---|---| | broker-integration /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 36 | Headless auth REST + Selenium , token lifecycle via live probing, order idempotency, per-broker rate limiting, borrow cost modeling, cost budgeting | | real-time-architecture /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 31 | Producer-consumer tick pipelines, burst-safe buffering, explicit backpressure policy, WebSocket subscription reconciliation after a reconnect | | backtesting-methodology /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 31 | Lookahead bias elimination, walk-forward validation, realistic slippage/fee/latency simulation, synthetic data generation, standardized tearsheets | | financial-ml /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 38 | Leakage-free feature engineering, offline-train/online-infer deployment, triple barrier labeler, sample weighting, model staleness detection | | risk-management /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 39 | Kill switches and drawdown circuit breakers, correlation-aware exposure limits, Kupiec test VaR backtesting, tail risk hedging, risk escalation matrices | | deployment-ops /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 30 | systemd process supervision, paper-to-live promotion checklist, IaC for trading hosts, canary releases, chaos engineering, secrets vault | | global-market-integration /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 44 | Crypto exchange APIs Binance/Coinbase/Kraken/Deribit/Bybit/OKX , FX OANDA/MT5 , CME Globex, Eurex, HKEX, SGX, ASX, JPX, CBOE, LSE, Xetra | | regulatory-compliance-global /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 38 | US SEC Rule 15c3-5, PDT, FINRA, EU MiFID II/RTS 6/MAR, UK FCA, ASIC, MAS, India SEBI, Canada IIROC, Hong Kong SFC, Japan FSA | | multi-asset-derivatives /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 28 | SPAN margin calculation, futures contract roll automation, real-time Greeks aggregation, perpetual futures funding rates, variance swaps, CDS, quanto options | | execution-algorithms /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 32 | TWAP/VWAP order slicing, POV execution, implementation shortfall minimization, iceberg detection, smart order routing SOR , dark pool routing, auctions | | data-management-global /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 37 | Global exchange holiday calendars, DST transition handling, multi-timezone session scheduling, multi-currency P&L, ISIN/CUSIP/SEDOL cross-referencing | | crypto-custody-security /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 29 | Wallet key custody, hot-cold split, withdrawal whitelisting, multi-sig approval, HSM integration, Shamir secret sharing, MPC custody | | portfolio-multi-strategy /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 28 | Cross-strategy correlation monitoring, performance-based capital reallocation, strategy retirement criteria, risk parity allocation, meta-strategy signal arbitration | | market-microstructure-latency /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 24 | Colocation latency budgets, PTP clock sync, tick-to-trade measurement, order book signals, adverse selection measurement, FPGA/microwave evaluation | | quant-research-alt-data /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 20 | Satellite imagery signals, credit card transaction data, web-scraped sentiment, supply chain networks, Google Trends, social media bot filtering, transcript NLP | | tax-accounting-reporting-global /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md | 16 | US wash sale tracking, FIFO vs specific-lot accounting, Section 475 MTM election, crypto tax lot tracking, 1099-B reconciliation, Section 1256 futures tax | Full searchable index: index.json /HimanshuJ16/Algo-Trading-Skills/blob/main/index.json . Every skill listed by domain with its trigger description: docs/ROADMAP 500.md /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/ROADMAP 500.md . The full library is roughly 3.5 million tokens of Markdown — far past any context window. Progressive disclosure is what makes it usable: an agent searches short descriptions to find the right skill, then loads only that one. | Stage | What the agent reads | Cost | |---|---|---| | Discover | index.json — name, description, domain and tags for every skill, queryable without touching a single skill file | ~250 tokens per skill as shipped ~80 for a name+description projection | | Load | The one matching SKILL.md — workflow, scope boundaries, pitfalls, verification | ~2,000-3,700 tokens median ~2,700 | | Go deeper | references/ and scripts/ for that skill only, once it is actually implementing | on demand | index.json is a single JSON object with a skills array and a subdomains count map, so an agent can filter by domain or grep descriptions and narrow the whole library to a handful of candidates before loading anything. User prompt: "My Fyers bot's live orders keep getting placed twice after a timeout" Agent's internal process: 1. Queries index.json descriptions for all 501 skills → identifies order-placement-idempotency and token-lifecycle-live-probing as top matches. 2. Loads top match: skills/order-placement-idempotency/SKILL.md → checks When NOT to Use first — this is order placement, not a cancel-request race, so the skill applies. → follows the structured Workflow section: classify timeout as ambiguous not failed , reconcile against broker order book before any retry. 3. Loads references/workflows.md for full sequence diagrams and scripts/order ledger.py for working helper logic. 4. Validates results using the Verification section → runs python -m unittest discover -s skills/order-placement-idempotency/scripts → confirms a simulated network timeout no longer produces duplicate executions. Without these skills, the agent guesses at retry logic and doubles order risk. With them, it follows the exact playbook a senior trading engineer would use. Every skill follows a consistent directory structure: skills/order-placement-idempotency/ ├── SKILL.md ← Skill definition YAML frontmatter + Markdown body ├── references/ │ ├── standards.md ← Broker/framework coverage + regulatory touchpoints │ └── workflows.md ← Deep technical procedure reference ├── scripts/ │ ├── order ledger.py ← Working reference implementation │ └── test order ledger.py ← Its unittest suite └── assets/ └── checklist.md ← Printable sign-off checklist Each helper is a standalone module — no imports from other skills, no shared package — so you can lift one file out of the repo and into your own codebase without dragging the library along. --- name: order-placement-idempotency description: - Use whenever a bot places, modifies, or cancels live orders and must guarantee it never double-executes an order due to retries, timeouts, or reconnects license: Apache-2.0 metadata: domain: algorithmic-trading subdomain: broker-integration tags: broker-integration, idempotency, client-order-id, order-ledger, retry-safety brokers frameworks: Fyers API v3; Zerodha Kite Connect; Upstox API v2; IBKR API version: "2.0.0" author: algo-trading-skills-contributors --- The agentskills.io specification https://agentskills.io/specification allows six top-level fields, so everything this repository adds lives under metadata: as string values. Two rules on description do the heavy lifting for discovery: it starts with "Use when …" the situation an agent is in, not a description of the subject , and it fits in 280 characters , because every installed skill's description is loaded into context on every session. Both are enforced by tools/validate skills.py /HimanshuJ16/Algo-Trading-Skills/blob/main/tools/validate skills.py , alongside the official agentskills validate . When to Use Trigger conditions — when should an AI agent activate this skill? When NOT to Use Scope boundaries — each excluded case handed to the skill that owns it. Prerequisites Required tools, access, and environment setup. Workflow Step-by-step execution guide with specific decision points. Common Pitfalls Named, specific failure modes this skill prevents. Verification How to confirm the skill was executed successfully, with a runnable command. Related Skills Cross-links to other skills in this repo. All seven sections are required. tools/validate skills.py /HimanshuJ16/Algo-Trading-Skills/blob/main/tools/validate skills.py enforces them in CI, along with the scripts/ layout and the runnability of every documented test command — see docs/skill-anatomy.md /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/skill-anatomy.md for the contract in prose and .github/workflows/validate-skills.yml /HimanshuJ16/Algo-Trading-Skills/blob/main/.github/workflows/validate-skills.yml for the pipeline. This repository includes native auto-discovery instructions for all major AI coding platforms: | Platform / Agent | Zero-Config Rule File | Auto-Discovery Standard | |---|---|---| | Claude Code | CLAUDE.md /HimanshuJ16/Algo-Trading-Skills/blob/main/CLAUDE.md + .claude-plugin/ /HimanshuJ16/Algo-Trading-Skills/blob/main/.claude-plugin | Anthropic Claude Code project + plugin marketplace convention | | OpenAI Codex CLI / OpenHands | AGENTS.md /HimanshuJ16/Algo-Trading-Skills/blob/main/AGENTS.md | Open cross-tool agent instruction format | | Gemini CLI | GEMINI.md /HimanshuJ16/Algo-Trading-Skills/blob/main/GEMINI.md | Google Gemini CLI project instructions | | GitHub Copilot | .github/copilot-instructions.md /HimanshuJ16/Algo-Trading-Skills/blob/main/.github/copilot-instructions.md | GitHub Copilot repo-level rules | | Cursor | .cursor/rules/algo-trading-skills.mdc /HimanshuJ16/Algo-Trading-Skills/blob/main/.cursor/rules/algo-trading-skills.mdc | Cursor MDC rule format | | Cline / Roo Code | .clinerules /HimanshuJ16/Algo-Trading-Skills/blob/main/.clinerules | Cline / Roo Code system rule | | Windsurf | .windsurfrules /HimanshuJ16/Algo-Trading-Skills/blob/main/.windsurfrules | Windsurf rule configuration | | Continue | .continue/rules/algo-trading-skills.md /HimanshuJ16/Algo-Trading-Skills/blob/main/.continue/rules/algo-trading-skills.md | Continue dev auto-discovery rule | | Aider | CONVENTIONS.md /HimanshuJ16/Algo-Trading-Skills/blob/main/CONVENTIONS.md / .aider.conf.yml /HimanshuJ16/Algo-Trading-Skills/blob/main/.aider.conf.yml | Aider project conventions | The table above lists the tools this repository ships a rule file for. Beyond those, the skills are plain SKILL.md directories in the agentskills.io https://agentskills.io format, so any agent or framework that reads that format can load them — point it at skills/ and it has everything it needs. To see how skills chain together in complete pipelines, explore the runnable walkthroughs in examples/ /HimanshuJ16/Algo-Trading-Skills/blob/main/examples : - examples/01 resilient order execution and circuit breaker.py /HimanshuJ16/Algo-Trading-Skills/blob/main/examples/01 resilient order execution and circuit breaker.py — Order idempotency + drawdown circuit breakers + live token probing. - examples/02 lookahead free backtest with slippage.py /HimanshuJ16/Algo-Trading-Skills/blob/main/examples/02 lookahead free backtest with slippage.py — Point-in-time signal engine + market impact slippage simulation + performance tear-sheet. - examples/03 cross strategy risk parity allocation.py /HimanshuJ16/Algo-Trading-Skills/blob/main/examples/03 cross strategy risk parity allocation.py — Rolling strategy correlations + risk parity rebalancing + automated strategy retirement. Cross-cutting maps live in mappings/broker-api-coverage.md /HimanshuJ16/Algo-Trading-Skills/blob/main/mappings/broker-api-coverage.md and mappings/regulatory-coverage.md /HimanshuJ16/Algo-Trading-Skills/blob/main/mappings/regulatory-coverage.md ; the system architecture the skills were extracted from is in docs/architecture.md /HimanshuJ16/Algo-Trading-Skills/blob/main/docs/architecture.md . This repository supports machine-discoverable documentation standards for LLMs and AI crawlers: - llms.txt /HimanshuJ16/Algo-Trading-Skills/blob/main/llms.txt — Concise index of core documentation, skill categories, and developer entrypoints. - llms-full.txt /HimanshuJ16/Algo-Trading-Skills/blob/main/llms-full.txt — Full architecture breakdown and domain mapping for large context windows. | Version | Highlights | |---|---| | v3.0.0 | Frontmatter migrated to the agentskills.io specification repo fields under metadata: , one Claude Code plugin per domain instead of one monolith, descriptions rewritten as "Use when …" triggers capped at 280 characters, duplicate skills merged, and CI extended with skills-ref , a Python version matrix, generated-file drift checks and the cookbook examples. See CHANGELOG.md /HimanshuJ16/Algo-Trading-Skills/blob/main/CHANGELOG.md . | | v2.0.0 | Reference implementations upgraded across the core broker, risk and real-time skills. | | v1.0.0 | Initial library across 16 engineering domains, with tools/validate skills.py and tools/run all tests.py enforced in CI. | This project grows through community contributions. Here is how to get involved: - Add a new skill — Follow the template and frontmatter structure enforced by tools/validate skills.py and submit a PR. - Improve existing skills — Update workflows, refine code engines, add unit tests, or extend regulatory mappings. - Report issues — Found an edge case or missing failure mode? Open an issue. Before opening a PR, run the gates locally. CI runs these plus the agentskills.io reference validator and the cookbook examples — see CONTRIBUTING.md /HimanshuJ16/Algo-Trading-Skills/blob/main/CONTRIBUTING.md how-the-library-is-verified for the full pipeline: python tools/validate skills.py python tools/run all tests.py python tools/build index.py --check regenerate and commit if this fails python tools/build marketplace.py --check python -m unittest discover -s tests The quality bar is in CONTRIBUTING.md /HimanshuJ16/Algo-Trading-Skills/blob/main/CONTRIBUTING.md , and it is a high one: would following this skill have prevented a real production bug, and is its Verification section actually checkable? A regulatory or broker-behaviour claim must be verifiable against an authoritative source — a missing claim is better than a wrong or fabricated one. Every PR is reviewed for technical accuracy and agentskills.io standard compliance. If you use this project in research or publications: @software{algo trading skills, author = {Jangir, Himanshu}, title = {Algo-Trading-Skills}, year = {2026}, url = {https://github.com/HimanshuJ16/Algo-Trading-Skills}, license = {Apache-2.0}, note = {501 structured algorithmic trading skills for AI agents, mapped to SEC Rule 15c3-5, Reg NMS, MiFID II, FCA, SEBI, and ISDA standards} } This project is licensed under the Apache License 2.0 /HimanshuJ16/Algo-Trading-Skills/blob/main/LICENSE . You are free to use, modify, and distribute these skills in both personal and commercial projects. If this project helps your quantitative trading work, consider giving it a ⭐ ⭐ Star · 🍴 Fork · 💬 Discuss · 📝 Contribute Community project by @HimanshuJ16 https://github.com/HimanshuJ16 . Not affiliated with Anthropic PBC or any broker referenced in this repository.