Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 86 961 files from 2 125 authors, of which 68 678 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Gather phase context through adaptive questioning before planning. Use --all to skip area selection and discuss all gray areas interactively. Use --auto to skip interactive questions (Claude picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).
Generate or update project documentation verified against the codebase
Route freeform text to the right GSD command automatically
Retroactively audit an executed AI phase's evaluation coverage — scores each eval dimension as COVERED/PARTIAL/MISSING and produces an actionable EVAL-REVIEW.md with remediation plan
Execute all plans in a phase with wave-based parallelization
Socratic ideation and idea routing — think through ideas before committing to plans
Extract decisions, lessons, patterns, and surprises from completed phase artifacts
Execute a trivial task inline — no subagents, no planning overhead
Post-mortem investigation for failed GSD workflows — analyzes git history, artifacts, and state to diagnose what went wrong
Import a GSD-2 (.gsd/) project back to GSD v1 (.planning/) format
Build, query, and inspect the project knowledge graph in .planning/graphs/
Diagnose planning directory health and optionally repair issues
Show available GSD commands and usage guide
Ingest external plans with conflict detection against project decisions before writing anything.
Scan a repo for mixed ADRs, PRDs, SPECs, and DOCs and bootstrap or merge the full .planning/ setup from them. Classifies each doc in parallel, synthesizes a consolidated context with a conflicts report, and routes to new-project or merge-milestone depending on whether .planning/ already exists.
Triage and review all open GitHub issues and PRs against project templates and contribution guidelines
Insert urgent work as decimal phase (e.g., 72.1) between existing phases
Join the GSD Discord community
Query, inspect, or refresh codebase intelligence files in .planning/intel/
Surface Claude's assumptions about a phase approach before planning
List active GSD workspaces and their status
Interactive command center for managing multiple phases from one terminal
Analyze codebase with parallel mapper agents to produce .planning/codebase/ documents
Generate a comprehensive project summary from milestone artifacts for team onboarding and review
Specialized guidance for migrating Node.js packages from the legacy Mocha, Sinon, and Istanbul/c8 ecosystem to Jest. It focuses on surgical test transformation, type safety, and resolving ESM/CommonJS interoperability issues.
Search 2500+ curated ChatGPT and LLM open-source repositories. Use when the user asks to find tools, libraries, or repos related to ChatGPT, LLMs, RAG, agents, langchain, NLP, AI development, or any open-source AI tooling.
Design documentation for the OpenZL component registry located under tests/registry. **USE AUTOMATICALLY** whenever editing files under tests/registry/.
How to mint real OpenZL frames and chunks for GPU decoder tests using the contrib/gpu/testkit utilities (frame_factory, multichunk_frame, frame_verifier), and how to extract a codec's encoded streams via reflection for differential GPU decode. USE when writing or reviewing GPU-decoder tests that need OpenZL-encoded fixtures.
Design patterns and requirements for OpenZL codecs (located under `src/openzl/codecs/`). **USE AUOMATICALLY** when creating, modifying, or reviewing codecs in OpenZL.
Use when creating benchmark scenarios for new openzl codec nodes in unitBench - adding kernel-level encode/decode benchmarks or graph-level compress/decompress benchmarks for codecs like bitsplit, delta, transpose, entropy, etc.
> Turn a mission or lab idea into a fully researched GitHub issue spec on microsoft/agent-academy, then post it with the GitHub CLI. Use this skill whenever the user wants to propose new Agent Academy content before writing it — course missions (Recruit, Operative, Commander), standalone Special Ops, or Cowork Collective missions. Trigger whenever the user says "write a spec for a mission", "create an issue for a new lab", "I want to propose a Special Ops", "file a mission proposal", "spec out a lab", "open an issue for a new module", or hands over Microsoft Learn documentation, interviewing for scope, repo reconnaissance and duplicate detection across both docs and existing issues, frontmatter and tag validation, writing-style conformance, drafting the issue body, title conventions, milestone and assignee metadata, and posting plus verifying the issue via `gh`.
> Scaffold and author content for the microsoft/agent-academy GitHub repo. Use this skill whenever the user wants to create a new mission, lab, or module for Agent Academy — whether that's a course mission (Recruit, Operative, Commander) or a standalone Special Ops mission. Trigger whenever the user says "write a mission", "scaffold a lab", "create a Special Ops", "new Agent Academy module", or describes an agent-building concept they want to turn into a hands-on lesson. Also trigger when the user says "add a module to agent academy", "I want to contribute a mission", duplicate detection, mission naming, markdown scaffolding, step-by-step content drafting, cross-linking, tag/category suggestions, difficulty rating, and badge image generation for Special Ops missions.
>- Helps employees identify available device options based on their needs, using the `Get Employee Assets` tool.
Use this skill when generating reports, tables, or email output to produce polished, self-contained, responsive HTML.
> Look up who has starred the microsoft/agent-academy repository on GitHub. Use this skill whenever the user wants to check stargazers, see if a specific GitHub user has starred the repo, or retrieve an up-to-date list of stargazers. Trigger whenever the user says "who starred agent academy", "check stargazers", "has <user> starred the repo", or asks anything about the repository's stargazer list. This skill uses the GitHub CLI to fetch stargazers via the GitHub API and saves the results to a local JSON file. It will install prerequisites if needed.
Use for any IT problem the user reports - login, Wi-Fi, device, app errors, or "it's not working". Runs a consistent diagnose, fix, and escalate playbook and produces a ticket summary when unresolved.
Generate a full Agent Academy feedback report — extracting feedback from Excel files and GitHub issues, analyzing sentiment, generating charts, and producing a single styled PDF with a cover page, management summary, and detailed analysis. Use this skill when the user asks to generate an Agent Academy report, create a feedback analysis, build a course completion report, or wants to analyze Agent Academy survey data. Also triggers when the user mentions Agent Academy feedback, course grades, sentiment analysis of Agent Academy data, or exporting Agent Academy results to PDF.
>- Helps employees identify available device options based on their needs, using the `Get Employee Assets` tool.
Generates a concise IT support ticket summary after troubleshooting paths have been exhausted.
>- Helps employees identify available device options based on their needs, using the `Get Employee Assets` tool.
Call this when a user states an IT issue and requests troubleshooting help. It provides step-by-step procedure for diagnosing and resolving IT issues, including escalation with a ticket summary.
>- Create a 1-hour Outlook follow-up meeting for pre-onboarding after a successful Docusign workflow trigger, using the employee name and agreement effective date from workflow context.
Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment setup, training-loop or other code authoring/scaffolding, contributor/CI/packaging questions, repo-specific questions in physicsnemo-sym/-cfd/-curator, or general (non-physics) ML/PyTorch.
> Fetch structured stock sentiment across Reddit, X.com, news, and Polymarket using the Adanos Finance API. Use this skill whenever the user asks how much people are talking about a stock, how hot a ticker is on social platforms, how many Polymarket bets exist for a company, whether sources are aligned, or "social sentiment on TSLA", "how hot is NVDA on X.com", "how many Reddit mentions does AAPL have", "compare sentiment on AMD vs NVDA", "how many Polymarket bets on Microsoft", "is Reddit aligned with X on META", "stock buzz", "bullish percentage", and any mention of cross-source stock sentiment research. This skill is READ-ONLY and does not place trades or modify anything.
> Query Fintel (fintel.io) institutional market intelligence (X-API-KEY header), or the official MCP server at rate/fee and shares available to borrow, daily short volume, fails-to-deliver (FTD), institutional ownership from SEC 13F filings, insider transactions from SEC Form 3/4/5, analyst price targets, ratings and forecasts, dividends and earnings history, earnings and dividend calendars, EOD price bars, last trade price, security master lookup by ticker/CUSIP/ISIN/FIGI, leaderboards, watchlists and alerts. borrow rate, cost to borrow, shares available to borrow, FTD, fails to deliver, short volume, 13F holders, institutional owners, who owns X, insider buying, insider selling, Form 4 transactions, analyst price target, days to cover, short interest ratio.
> comps, earnings previews/recaps, sector deep-dives, SEC filings, transcripts, supply-chain mapping, ownership flow, macro framing) via FUNDA_API_KEY for raw data (real-time quotes, intraday candles, EOD prices, financial statements, options chains/greeks/GEX, supply-chain KG, social sentiment, news, calendars, FRED, ESG, congressional quote, stock price, intraday, balance sheet, income statement, options chain, DCF, comps, earnings preview/recap, analyst estimates, 10-K/10-Q/8-K, transcript, ownership flow, gamma exposure, supply chain, sector deep-dive, congressional trades, FRED. Prefer MCP for synthesis/analysis questions; use REST for raw structured data the MCP declines.
> Check the current status of the Strait of Hormuz — shipping transit data, oil price impact, stranded vessels, insurance risk levels, diplomatic developments, and global trade impact. Use this skill whenever the user asks about the Strait of Hormuz, Hormuz chokepoint, Persian Gulf shipping risk, oil transit disruption, war risk premium in the Gulf, Middle East shipping routes, tanker traffic through Hormuz, oil supply chain risk, or geopolitical risk affecting energy markets. "oil chokepoint", "Persian Gulf tanker traffic", "war risk premium", "Hormuz crisis", "energy supply chain risk", "oil transit disruption", "Middle East shipping", any mention of Hormuz or Persian Gulf in context of oil, shipping, or geopolitical risk.
> Read Hyperliquid (app.hyperliquid.xyz) perp + spot market data via opencli (read-only, public info API). Use whenever the user wants Hyperliquid perpetual or spot markets, mark/oracle/mid prices, 24h change, funding rates (hourly or annualized APR), open interest, volume, the L2 order book, OHLCV candles, historical funding, or a cross-venue funding comparison (Hyperliquid vs Binance vs Bybit) for funding "funding on BTC perp", "Hyperliquid order book", "HL open interest", "funding arb Hyperliquid vs Binance", "Hyperliquid candles for SOL", "Hyperliquid spot markets", "PURR price on Hyperliquid", "hyperliquid", "hyperliquid.xyz", "HL DEX". READ-ONLY market data — no account, order, or trade operations.
> Read TradingView desktop app for market data, news, alerts, watchlists, and screener results using opencli (read-only). Use this skill whenever the user wants quotes, options chains, options expiries, screener results across stocks/crypto/forex/futures/bonds, gainers/losers/movers, news headlines or full story bodies, alerts (active list, fire log, offline fires), watchlists including colored flag lists, symbol search/autocomplete, chart state, or screenshots X", "IV on Y", "show me SNDK puts", "TV screener for Y sector", "screen oversold stocks", "TV gainers", "crypto by market cap", "TradingView news on AAPL", "show my watchlists", "red flag list", "list my alerts", "what alerts fired", "search TV for nvidia", "what symbol is on my chart", "screenshot NVDA chart", "TradingView IV skew", "TV expiries for X". This skill is READ-ONLY — it does NOT place trades, modify watchlists, or change chart layouts.
> Estimate the intrinsic value of a public company using DCF, relative (peer multiple) and sum-of-parts (SOTP) methods, then triangulate to an implied share price with "what is AAPL worth", "valuation of NVDA", "fair value of TSLA", "intrinsic value", "DCF for MSFT", "build a DCF", "discounted cash flow", "WACC", "terminal value", "implied share price", "upside to fair value", "is X overvalued/undervalued", "relative valuation", "peer comparison valuation", "EV/EBITDA target", "SOTP", "sum of the parts", "how much is [company] worth", "price target from fundamentals", "value this company", or any ticker in the context of computing intrinsic or relative valuation. Default to running ALL three methods (DCF + relative + SOTP-if-applicable) and presenting a blended implied price with a sensitivity table. Do not answer valuation questions from memory — always run the workflow.
> Generate a pre-earnings briefing for any stock using Yahoo Finance data. Use this skill whenever the user wants to prepare for an upcoming earnings report, understand what analysts expect, review a company's beat/miss track record, or get a quick overview before an earnings call. "MSFT reports next week", "earnings preview", "pre-earnings analysis", "what are analysts expecting for NVDA", "earnings estimates for", "will GOOGL beat earnings", "earnings beat/miss history", "upcoming earnings", "before earnings", "earnings setup", "consensus estimates", "earnings whisper", "EPS expectations", "what's the street expecting", "earnings season preview", any mention of preparing for or previewing an earnings report, or any request to understand expectations ahead of a company's earnings date. Always use this skill when the user mentions a ticker in context of upcoming earnings, even if they don't say "preview" explicitly.
> Generate a post-earnings analysis for any stock using Yahoo Finance data. Use when the user wants to review what happened after earnings, understand beat/miss results, see stock reaction, or get an earnings recap. "did NVDA beat earnings", "post-earnings analysis", "earnings surprise", "what happened with GOOGL earnings", "earnings reaction", "stock moved after earnings", "EPS beat or miss", "revenue beat or miss", "quarterly results for", "how were earnings", "AMZN reported last night", "earnings call recap", or any request about a company's recent earnings outcome. Use this skill when the user references a past earnings event, even if they just say "AAPL reported" or "how did they do".
> Deep-dive into analyst estimates and revision trends for any stock using Yahoo Finance data. Use when the user wants to understand analyst estimate direction, how EPS or revenue forecasts changed over time, compare estimate distributions, or analyze growth projections across periods. "EPS revisions for TSLA", "how have estimates changed for MSFT", "estimate revisions", "EPS trend", "revenue estimates", "consensus changes", "analyst estimates", "estimate distribution", "growth estimates for", "estimate momentum", "revision trend", "forward estimates", "next quarter estimates", "annual estimates", "estimate spread", "bull vs bear estimates", "estimate range", or any request about tracking or comparing analyst estimates/revisions. Use this skill when the user asks about estimates beyond a simple lookup — if they want context, trends, or analysis, this is the right skill.
> Calculate ETF premium/discount vs NAV via Yahoo Finance, and decompose single-day surges into NAV-driven vs structural components (gamma squeeze, dealer hedging, blocked AP arbitrage). Use whenever the user asks about an ETF's premium or discount, NAV comparison, why an ETF diverged from its holdings, or how much of a move is dealer-hedging-driven. "IBIT premium", "bond ETF discount", "trading above/below NAV", "ETF premium screener", "biggest discount", "compare ETF NAV", "ETF arbitrage", "ETF gamma squeeze", "ETF premium surge", "decompose ETF move", "dealer gamma exposure", "GEX for ETF", "why did this ETF jump", "premium convergence", "AP arbitrage blocked", or any request about the gap between an ETF's price and underlying value. Especially relevant for leveraged, inverse, international, bond, commodity, and crypto ETFs.
> Generate an interactive options payoff curve chart with dynamic parameter controls. Use this skill whenever the user shares an options position screenshot, describes an options strategy, butterfly, spread (vertical/calendar/diagonal/ratio), straddle, strangle, condor, covered call, protective put, iron condor, or any multi-leg options structure. Also triggers when a user pastes strike prices, premiums, expiry dates, or says things like "show me the payoff", "draw the P&L curve", "what does this trade look like", or uploads a screenshot from a broker (IBKR, TastyTrade, Robinhood, etc). Always use this skill even if the user only provides partial info — extract what you can and use defaults for the rest.
> Analyze SaaS company valuation compression between funding rounds. Use this skill between rounds, why the ARR multiple compressed or expanded, comparing a company's compression to macro benchmarks, or explaining what drove valuation changes for any VC-backed software company. Trigger on phrases like "valuation compression", "ARR multiple", "round-to-round valuation", "multiple change", or when the user asks to compare a company's funding rounds. Always use this skill for any multi-round SaaS valuation analysis — do not try to answer from memory alone.
> Analyze stocks using Mark Minervini's SEPA (Specific Entry Point Analysis) methodology. Use this skill whenever the user mentions SEPA, Minervini, superperformance, trend template, VCP (Volatility Contraction Pattern), Stage 2 uptrend, stage analysis, pivot point breakout, or asks about growth stock screening criteria. Also triggers when the user wants to evaluate whether a stock meets swing trading entry criteria, check moving average alignment (bullish calculate position sizing based on risk percentage, or identify consolidation patterns like cup-with-handle, flat base, bull flag, or high tight flag. Use this skill even when the user simply asks "should I buy this stock" or "is this a good setup" in the context of growth/momentum trading, or when they share a stock chart and want pattern analysis.
> Analyze stock correlations to find related companies and trading pairs. Use when the user asks about correlated stocks, related companies, sector peers, trading pairs, or how two or more stocks move together. "correlation between AAPL and MSFT", "what moves with", "sector peers", "pair trading", "correlated stocks", "when NVDA drops what else drops", "stocks that move together", "beta to", "relative performance", "supply chain partners", "correlation matrix", "co-movement", "related tickers", "sympathy plays", "semiconductor peers", "hedging pair", "realized correlation", "rolling correlation", or any request about stocks that move in tandem or inversely. Also triggers for well-known pairs like AMD/NVDA, GOOGL/AVGO, LITE/COHR. If only one ticker is provided, infer the user wants correlated peers.
> Analyze stock liquidity using bid-ask spreads, volume profiles, order book depth, market impact estimates, and turnover ratios via Yahoo Finance data. Use this skill whenever the user asks about liquidity, trading costs, bid-ask spread, market depth, volume analysis, slippage, market impact, turnover ratio, or how easy/hard it is to trade a stock without moving the price. "market impact of a large order", "turnover ratio", "slippage estimate", "can I trade 100k shares without moving the price", "liquidity comparison", "spread analysis", "ADTV", "Amihud illiquidity", "dollar volume", "execution cost estimate", "liquidity score", penny stocks, small caps, or thinly traded securities.
> Fetch financial and market data using the yfinance Python library. Use this skill whenever the user asks for stock prices, historical data, financial statements, options chains, dividends, earnings, analyst recommendations, or any market data. "get me the financials", "show earnings", "what's the price of", "download stock data", "options chain", "dividend history", "balance sheet", "income statement", "cash flow", "analyst targets", "institutional holders", "compare stocks", "screen for stocks", or any request involving Yahoo Finance data. Always use this skill even if the user only provides a ticker — infer intent from context.
Claude Skills — questions
Answers built from the skills we actually parsed.