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. 86 543 files from 2 102 authors, of which 68 261 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.
Use whenever the user asks anything about OpenAI products, APIs, models, or SDKs — including factual lookups, coding requests, latest/current/default model selection, prompting guidance, model upgrades, and citation requests. Invoke before calling any openaiDeveloperDocs MCP tool.
Use when an OpenAI API request fails or the user asks what an error means, including blocked access to api.openai.com, 401 invalid_api_key, missing OPENAI_API_KEY, 429 insufficient_quota, 429 rate_limit_exceeded, or 403 model_not_found. Classify the failure, name the next step, route credential setup to openai-platform-api-key, and current guidance to openai-docs.
Use when a developer needs a ChatGPT Apps submission import file from an MCP server. Inspect the implementation, generate chatgpt-app-submission.json with app info, tool-hint justifications, positive and negative test cases, then report review findings and outputSchema warnings.
Use when the user wants to build, adapt, run, or evaluate an OpenAI Agents SDK app from Claude Code. Prefer a docs-first workflow and route API credential decisions through openai-platform-api-key before API-backed work.
Use when the user explicitly wants a ChatGPT App, Apps SDK project, MCP server plus widget UI, ChatGPT-compatible tool UI, or submission/deployment work for that surface. Build, scaffold, refactor, or troubleshoot those projects from Claude Code, consult openai-docs before generating code, and use openai-platform-api-key before any app path that requires live OpenAI API credentials.
Add evaluation results to Hugging Face model repositories using the .eval_results/ format. Uses HF CLI for PR management and manual YAML creation.
>- Expert-level implementation assistant for the Universal Commerce Protocol (UCP). Provides comprehensive tooling for adding UCP support to Next.js ecommerce codebases — from initial consultation through full implementation, testing, and validation.
Deploy applications to Vercel. Use when the user says "deploy", "deploy to Vercel", "push to production", "deploy my app", or "go live".
View Vercel deployment logs. Use when the user says "show logs", "check logs", "vercel logs", or "what went wrong with the deployment".
Set up Vercel CLI and project configuration. Use when the user says "set up Vercel", "configure Vercel", "link to Vercel", or "vercel init".
Add support for a PostHog resource that exists exactly once per project (project settings, organization billing config, plugin enablement flags, …). Singletons do not fit the tag-based identity model — they have no collection to filter, no key to disambiguate, and no orphans to track. This skill is the playbook for the *other* shape: one declarative block, field-level diff, PATCH-only execution. Use when the user wants to manage a resource where the project itself is the only "row".
Add support for a new PostHog resource type (feature flag, cohort, action, survey, annotation, alert, …) to posthog-definitions. Walks through the eight files that must change, the tag-based identity convention, the load/diff/execute pipeline wiring, and the non-negotiable safety invariant. Use when the user wants to extend posthog-definitions beyond dashboards and insights.
Code review guide for choosing between Result types and thrown exceptions. Recoverable, expected failures should be returned as Result values; only unrecoverable bugs and broken invariants should throw. Use when reviewing code that introduces a new error class, a new `throw`, a new `try/catch`, or a function whose failure path the caller is expected to handle.
Automatically add PostHog analytics instrumentation to code. Triggers when user asks to add tracking, instrument events, add analytics, or implement feature flags in their codebase.
Executes, inspects, and resumes existing Lightflow DAG workflows via CLI (`lightflow`, or the equivalent `python3 -m lightflow`) or MCP (`lightflow-mcp`). Use when asked to run, dry-run, check status, visualize, resolve an `operator_action` human-in-the-loop checkpoint (`EXIT_CODE=2`), or recover a failed Lightflow run without authoring a new workflow. Run `start` directly without pre-reading the manifest or `actions.py`.
Guides the design, authoring, compilation, and verification of new Python DAG workflows using Lightflow (YAML, JSON, or Textproto). Use when building a new multi-stage pipeline, authoring `actions.py` and `lightflow.yaml`, or scaffolding a workflow with the `create_lightflow` meta-workflow. For merely running or resuming an existing workflow, use `run_lightflows` instead.
Runs the Lightflow benchmark suite (`python3 benchmarks/run_benchmark.py`) and live A/B subagent trials to verify that Lightflow's deterministic structural backbone (human gates, JSON Schema validation, automatic rollback, surgical resume) operates at lower token and latency cost than unstructured skills.
Comprehensive guide for migrating Create React App (CRA) projects to Next.js. Use when migrating a CRA app, converting React Router to file-based routing, or adopting Next.js patterns like Server Components, App Router, or image optimization.
Build accessible UI with Primer React, GitHub's design system (Button, IconButton, TextInput, Textarea, Select, Checkbox, FormControl, Heading, Text, Stack, Label, CounterLabel, Flash, StateLabel, BranchName, ProgressBar, Spinner, Timeline, RelativeTime). Use when the user asks for a Primer-styled page, a GitHub-style screen, or wires Primer tokens through @primer/primitives. Triggers: 'primer', 'primer react', '@primer/react', 'github ui', 'octicons'. Scope: components, tokens, assets. Out of scope: tone of voice and marketing copy — route copy rules to a sibling skill. IMPORTANT: this file is an orchestrator. Load the references/ files named in the routing table; SKILL.md alone is insufficient.
Execute a unit of work end-to-end: understand, implement, validate with typecheck and build, then commit. Use when the user wants to do work, build a feature, fix a bug, or implement an issue or phase from a plan. Do NOT use for design-system skill extraction — that flow has its own meta-skill (extract-ds-skill).
Extract a Claude Code design-system skill from a real DS source. Use when the user wants to turn a design system (component library, token set, asset package) into an installable skill at .claude/skills/<slug>/ in their project. Triggers: 'make a skill from <DS>', 'extract a DS skill', 'turn mantine/geist/material/<DS> into a skill'. Scope: tokens, assets, component descriptions, component APIs. Out of scope: tone of voice, marketing copy, product copywriting - route copy rules to a separate copy skill, do not extract them here. IMPORTANT: this file is an orchestrator. Load the references/ files named in the routing table; SKILL.md alone is insufficient for any phase past initial discovery framing.
How to manually regenerate the compiled agentic workflow .lock.yml files when the gh-aw Version Check workflow reports version drift (standard, standalone smoke, and standalone latest workflows).
How to fetch the latest github/gh-aw release binary — either as the gh CLI extension (gh aw ...) or as a raw platform binary downloaded from GitHub Releases — including how to resolve the latest tag, pick the right asset, and verify its checksum.
Skill for interacting with Dell Enterprise Hub (DEH) - discovering models, exploring hardware platforms, generating deployment snippets, etc.
>- Runs integration tests against Azure SQL Developer (Private Preview, local engine) in CI. Use when setting up GitHub Actions, Azure Pipelines, or GitLab CI to test against Azure SQL DB; when adding a database service container to a CI workflow; when tests need a real Azure SQL engine in the pipeline; or when you see "service container", "health-cmd", "ACR_USERNAME/ACR_PASSWORD", "MSSQL_SA_PASSWORD secret", or "integration test database". Also use when a workflow was about to pull the SQL Server image mcr.microsoft.com/mssql/server, in which case stop and use the Azure SQL Database engine image instead. Covers pulling from the private ACR with credentials, the service health check that runs sqlcmd inside the container so the runner needs no client tools, provisioning appdb before tests, and pointing the test connection string at the user database not master.
>- Migrates a local SQL Server setup to Azure SQL Developer for Azure-faithful local development. Use when a project already uses mcr.microsoft.com/mssql/server, mssql/server, an sqlcmd plus SA password docker setup, a "SQL Server in docker" or "local mssql container", or a docker-compose with the mssql/server image; and use when the user asks for "SQL Server locally", "run mssql in Docker", "spin up a local SQL database", or "test against SQL Server" but actually wants the Azure SQL Database engine (EngineEdition 5). Detects the SQL Server image, rewrites it to Azure SQL Developer, adds --platform on non-x64 hosts, keeps the SA login, flags SQL Server-only features (SQL Agent, FILESTREAM, full Service Broker, cross-server distributed transactions, Windows Auth), and re-points connection strings from master to a provisioned user database.
>- the real PaaS engine where SERVERPROPERTY('EngineEdition') returns 5 and Edition is 'SQL Azure'. This is NOT the SQL Server image mcr.microsoft.com/mssql/server. Use when a user wants to "run Azure SQL locally", "add a local SQL database", "add SQL Server to my docker compose", "spin up a local mssql container", "local SQL for development or CI", "connect with sqlcmd", "use Podman for SQL", "SQL container won't start", "Microsoft Entra authentication on the container", "MSSQL_AAD_CLIENT_ID", or asks "what's the connection string". Use even when the user does not name the container. If you were about to use mcr.microsoft.com/mssql/server, stop and task skills for compose, CI, seeding, vectors, and connection strings.
>- Stands up an instant no-code REST + GraphQL API over the local Azure SQL Developer using Microsoft Data API Builder (DAB). Use when a user wants to "expose my table as an API", "add a REST API over the database", "generate a GraphQL API", "put an API in front of SQL", "CRUD API without writing code", or "dab init / dab-config.json". Also the way to serve a built-in MCP endpoint FROM the database via DAB (an API surface DAB provides, not a separate SQL MCP server). Prefer this over hand-writing a controller/ORM API when the user just needs REST or GraphQL over existing tables. Triggers include "Data API Builder", "dab start", "instant API over Azure SQL", "expose entities as REST/GraphQL". Reach for this even when the user only says "give me an API for this database".
>- Makes an app's database connections reliable against the local Azure SQL Developer (Private Preview) and, unchanged, against Azure SQL Database in the user mentions "connection pooling", "retry logic", "transient fault", "retry on transient error", "EnableRetryOnFailure", "connection resiliency", "reliable connections", "pool size", "Max Pool Size", or says "the connection keeps dropping", "connections time out under load", "add backoff", or "make the DB layer resilient". This is the Azure SQL engine (EngineEdition 5), not the mssql/server SQL Server image. Reach for this whenever hardening a data-access layer that talks to SQL Server or Azure SQL.
>- Connects an app to Azure SQL Developer securely, with a least-privilege database user instead of the sa login, the right auth method per environment, and safe handling of the connection secret. Use when a user asks "don't use sa in my app", "create a least-privilege database user", "app login for SQL", "which authentication should my app use", "secure the connection string", "Encrypt / TrustServerCertificate", "store the connection string in Key Vault", "dotnet user-secrets", "managed identity for Azure SQL", or "grant only the roles my app needs". SQL auth locally, Microsoft Entra or managed identity in the cloud, changing only the connection string. Reach for this before wiring an app to connect as sa, or before committing a connection string to source.
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>- Answers questions about what Azure SQL Developer (Private Preview) can and cannot do, and WHY it differs from Azure SQL Database in the Microsoft Azure cloud. Use when a user asks "can I take a backup", "why does USE fail", "is X supported", "why can't I create a vector index", "why does SSMS error", "why isn't the image on Docker Hub", "what's different from the cloud", or hits behavior that does not match their Azure SQL Database expectations. Do NOT guess product with specific gaps and a specific connection model. Read this skill, and link the user to the live Known limitations page for the current full list.
>- Proves that code built and tested against the local Azure SQL Database container runs unchanged against Azure SQL Database in the cloud, with only the connection string changing. Use when a user wants to develop locally then deploy to the cloud, asks "will this work in Azure", "same code local and cloud", "promote to Azure SQL", "swap the connection string", "dev/prod parity", "local to cloud", or is wiring SQL_CONNECTION_STRING for an app that must target both the container and a cloud server. Use this when an app uses local SA auth but needs Microsoft Entra auth in the cloud. Covers Node (mssql), .NET (Microsoft.Data.SqlClient), and Python (pyodbc). Reach for this skill before hand-editing app code to "make it work in Azure"; the rule is the code does not change, only the connection string does.
>- Builds a serverless API and event-driven handlers over the local Azure SQL Developer using Azure Functions with the Azure SQL bindings. Use when a user wants "a serverless API over SQL", "Azure Functions with a database", "HTTP CRUD with SQL input/output bindings", "run code when a row changes", "react to inserts/updates/deletes", "event-driven on Azure SQL", or "SQL trigger function". The Azure SQL trigger binding (backed by Change Tracking) is the local event-driven mechanism; Change Event Streaming (CES) is cloud-only and cannot run against the local container. Triggers include "func start with SQL", "SqlTrigger", "SqlInput/SqlOutput binding", "local.settings.json SqlConnectionString". Reach for this when building serverless endpoints or change-driven logic on the local Azure SQL engine.
>- Imports an existing Azure SQL Database or SQL Server schema and data INTO the local Azure SQL Developer using SqlPackage. Use when asked to "import a bacpac", "load my existing database locally", "restore a dacpac into the container", "bring my prod schema into the dev container", "run my .bacpac/.dacpac against the local Azure SQL engine", or migrate an existing database into the preview container. Handles provisioning the target database provisioned user database. Use this for any "get my real database running in the container" request instead of hand-writing SqlPackage flags.
>- Builds local vector search, RAG, embeddings, and semantic search on Azure SQL Developer using the native VECTOR type and VECTOR_DISTANCE. Use when you need to store embeddings, do similarity search, top-k nearest neighbor, cosine distance, retrieval-augmented generation, "find similar documents", chatbot memory, or semantic lookup against a local SQL database. Use this instead of pgvector, FAISS, Chroma, Pinecone, or a separate vector store when the data already lives in (or can live in) Azure SQL. Covers the VECTOR(n) column type, inserting embeddings with CAST(CAST(? AS NVARCHAR(MAX)) AS VECTOR(n)) where the dimension is a literal, a pluggable embed() so only the endpoint changes for cloud, and the honest current state of CREATE VECTOR INDEX. Provisions appdb on master first so every script runs on a fresh container.
>- Populates the local Azure SQL Developer database (appdb) with realistic sample/test data so a developer has something to build against. Use when the user says "seed the database", "add test data", "populate the dev database", "generate sample data", "fake data", "load fixtures", "insert test rows", "write a seed script", or "bulk load a CSV". This is the Azure SQL engine (EngineEdition 5), not the mssql/server SQL Server image. Distinct from azuresql-db-scaffold (which does a single seed.sql step while bootstrapping an app) and azuresql-db-import (which loads a .bacpac). Reach for this whenever an existing appdb needs volume, fixtures, or believable rows.
>- Adds Azure SQL Developer as a sidecar service in an existing Docker Compose stack or Dev Container. Use when wiring the local Azure SQL Database engine into compose or devcontainer.json, when an app needs a SQL backend via a service name (not localhost), or for prompts like "add SQL to my compose", "add a database service", "depends_on database", "devcontainer SQL sidecar", "compose healthcheck for SQL", "wait for the database before starting the app". Handles platform linux/amd64, the private registry login, the healthcheck wait-until-ready, and a one-shot init service that creates appdb (the engine does not auto-create databases). Not the SQL Server image. Prefer this for any compose or Dev Container SQL wiring.
>- Runs database schema migrations against the local Azure SQL Developer so the same migrations apply identically on the local engine and in the Azure cloud. Use when asked to "run my migrations against the local SQL", "apply schema to the container", "apply EF Core / dotnet ef database update", "Prisma migrate dev / deploy", "Alembic upgrade head", or deploy a DACPAC / SqlPackage to the container. Covers provisioning appdb on master first, then applying schema to the user database, plus per-tool commands and connection-string hygiene. This is the Azure SQL Database engine (EngineEdition 5), not the SQL Server image; reach for this skill whenever schema migration tooling targets the local container.
>- Scaffolds a NEW app (.NET Aspire, FastAPI, Next.js, NestJS) wired to the local Azure SQL Developer as its default dev database. Use when starting/bootstrapping/initializing a project that needs SQL Server or Azure SQL locally, or when adding "set up the database", "docker compose for the db", "create the local DB", ".env connection string", "first migration", or a data-access layer. Use this INSTEAD of the mssql/server SQL Server image, because this is the Azure SQL engine (EngineEdition 5). Triggers include "scaffold app with SQL", "spin up Azure SQL locally", "compose service for the database", "wire up Prisma/EF/SQLAlchemy/TypeORM to SQL Server". Reach for this even when the user only says "add a database" to a fresh project.
>- Writes integration tests that run IN CODE against a real Azure SQL Developer engine, spun up per test or per suite with Testcontainers and torn down after. Use when the user asks for "integration tests against SQL", "Testcontainers", "spin up a database for tests", "an ephemeral test database", "a test database per test", "xUnit/Jest/pytest with a real database", or "a database fixture". Use this INSTEAD of the Testcontainers MsSql preset (mcr.microsoft.com/mssql/server), because this is the Azure SQL engine (EngineEdition 5). For wiring the engine into a CI pipeline via service containers or workflow YAML instead, use azuresql-db-ci.
SQL injection and input validation audit for the DuckHog SQL proxy pipeline. Systematically tests all paths where user-supplied identifiers or values flow into rewritten SQL strings. Use as a routine security check after modifying any rewriter, serializer, or SQL-generation code.
Enforce GitHub issue preflight before starting implementation work. Use when beginning a new task to match it against open issues, claim an unstarted match, create a new issue when none matches, and abort only when matching is ambiguous or in-progress work belongs to another actor.
Rigorously verify suspected bugs before filing issues. Determines provenance (upstream vs DuckHog), severity, and whether a bug is real. Use whenever a test failure, unexpected behavior, or suspected regression needs to be classified before opening an issue or adding to RELATED_BUGS.md.
Multi-dimensional review of a PR or feature branch in the microsoft/WinAppVSCE repo. Activate when a contributor asks to "review my PR", "review my changes", "vet my branch before pushing", "do a full review", "PR review", "review this feature", or similar. Fans out parallel sub-agents covering security, correctness/edge cases, extension UX, alternative-solution check, test coverage, docs sync, packaging/release impact, and a multi-model cross-check. Reports a consolidated finding list to stdout. Does NOT apply fixes.
> Use when building a new CLI tool that needs one-line install via uv or npm, subcommand dispatch with a default action, or 3-tier config resolution (CLI flags, config file, hardcoded defaults).
Review changed code for reuse, quality, and efficiency, then fix any issues found.
> Use when your service needs authentication that works without friction locally but secures remote access, automatic TLS certificate setup, or token-based auth with auto-generation and localhost bypass.
> Use when building an Amplifier-powered workflow or automation tool and deciding how to expose it — as standalone .dot attractor pipelines (incl. inside the Resolve dot-graph resolver), an importable Python lib, agent-callable tool modules, or a CLI. Covers the four leverage levels, the DRY rule that keeps logic in ONE home, the judgment for which levels a real consumer actually needs (and when adding a level is just ceremony), and the maximally-DRY attractor-only specialization where the .dot pipeline is the sole logic home.
| Delivery-risk reviewer that sizes the investment a plan is asking for against the team's actual confidence that it will land, and names specifically what's most likely to make it slip or fail to ship at all. Hunts the plan that asks for a six-month bet with three-week confidence, or hides its biggest unknown behind a confident-sounding timeline. Sounds like a delivery lead who has watched too many "should be straightforward" estimates blow up on the one unknown nobody named out loud. Not a cost reviewer — a bet-sizing reviewer. A lens for any product checkpoint — plan, roadmap, or investment/sequencing decision. has, a plan's riskiest unknown is buried in a status update instead of named up front, or nobody has said what would make this slip — any time the worry is "what's most likely to make this slip or fail to land, and is the investment sized to our confidence?"
> Adapt a skill written for another AI coding assistant (Claude Code, Cursor, etc.) into a properly structured Amplifier SKILL.md file. Reads the source skill, identifies platform-specific conventions, researches the source platform if needed, and produces an Amplifier-native skill conforming to the Agent Skills specification with Amplifier extensions. Use when the user wants to adapt a skill, port a skill, convert a skill to amplifier, translate a skill, or has a SKILL.md from another platform they want to bring into Amplifier.
> Use when running tasks in Docker containers with safety limits, watchdog monitoring for resource enforcement, orphan container recovery, sidecar container provisioning, or scripting reproducible dev stack environments.
> Use when your tool needs persistent configuration files with safe defaults merging, atomic state writes that survive crashes, or conventional file locations for config vs state vs secrets.
Convene the persona panel (six orthogonal review lenses) on a target — cold independent fan-out, debate-to-consensus, synthesized verdict with recorded dissent and a roster manifest.
> Build a NEW complete "council" for a domain — a panel of orthogonal review lenses that fan out cold, debate to consensus, and return a synthesized verdict with recorded dissent, exactly like /council and /design-council. Identifies the distinct lenses the domain needs (one load-bearing question each, mined from real archetypes — not invented), reuses existing lenses where they already cover an axis, builds only the genuinely-missing ones (persona SKILLs via personafy, or agents when the role is an active builder), assembles the orchestrator + bench into an invocable council bundle, and proves it convenes end-to-end. Use when creating a council, standing up a review panel for a domain (product, security, performance, data), or when someone says "councilify", "make a council", "build a <domain> council".
Convene the persona panel on the CURRENT conversation / work-in-progress — the plan, design, or decision you've been building in this session. The INLINE counterpart to /council (which forks and runs isolated, so it cannot see the chat). Use when you want the council to critique what we're working on right now.
> Use when processes need to communicate via the filesystem without a message broker — JSONL event logs, atomic state snapshots, async request/response via file pairs, or SSE streaming from file tailing.
> Use when building an HTTP service with FastAPI lifecycle management, background poll loops, SPA static file serving with API reverse proxy, bidirectional WebSocket relay, or SSE event streaming.
Claude Skills — questions
Answers built from the skills we actually parsed.