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. 79 404 files from 1 741 authors, of which 61 763 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 this skill when someone wants to learn GitHub Copilot CLI from scratch. Offers interactive step-by-step tutorials with separate Developer and Non-Developer tracks, plus on-demand Q&A. Just say "start tutorial" or and uses CLI-specific tools (ask_user, sql, fetch_copilot_cli_documentation).
Technology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.
Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.
Use Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.
Retrieve and display GitHub Copilot usage metrics for organizations and enterprises using the GitHub CLI and REST API.
Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
Prompt for generating an AGENTS.md file for a repository
Create an Architectural Decision Record (ADR) document for AI-optimized decision documentation.
Create a formal specification for an existing GitHub Actions CI/CD workflow, optimized for AI consumption and workflow maintenance.
Create GitHub Issue for feature request from specification file using feature_request.yml template.
Create GitHub Issues from implementation plan phases using feature_request.yml or chore_request.yml templates.
Create GitHub Issues for unimplemented requirements from specification files using feature_request.yml template.
Create GitHub Pull Request for feature request from specification file using pull_request_template.md template.
Create a new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Create an llms.txt file from scratch based on repository structure following the llms.txt specification at https://llmstxt.org/
Create a README.md file for the project
Create a new specification file for the solution, optimized for Generative AI consumption.
Create Spring Boot Java Project Skeleton
Create Spring Boot Kotlin Project Skeleton
Create time-boxed technical spike documents for researching and resolving critical development decisions before implementation.
Create a tldr page from documentation URLs and command examples, requiring both URL and command name.
Discovers all projects in a .NET solution, classifies each for Oracle-to-PostgreSQL migration eligibility, and produces a persistent master migration plan. Use when starting a multi-project Oracle-to-PostgreSQL migration, creating a migration inventory, or assessing which .NET projects contain Oracle dependencies.
Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.
Creates integration test cases for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Generates DB-agnostic xUnit tests with deterministic seed data that validate behavior consistency across both database systems. Use when creating integration tests for a migrated project, generating test coverage for data access layers, or writing Oracle-to-PostgreSQL migration validation tests.
Get best practices for C# async programming
Ensure that C# types are documented with XML comments and follow best practices for documentation.
Generate a complete MCP server project in C# with tools, prompts, and proper configuration
Get best practices for MSTest 3.x/4.x unit testing, including modern assertion APIs and data-driven tests
Get best practices for NUnit unit testing, including data-driven tests
Get best practices for TUnit unit testing, including data-driven tests
Get best practices for XUnit unit testing, including data-driven tests
Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.
Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.
Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices
Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.
Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations
Triage and resolve Debian Linux issues with apt, systemd, and AppArmor-aware guidance.
Complete development kit for Microsoft 365 Copilot declarative agents with three comprehensive workflows (basic, advanced, validation), TypeSpec support, and Microsoft 365 Agents Toolkit integration
>- Comprehensive guide for configuring and managing GitHub Dependabot. Use this skill when users ask about creating or optimizing dependabot.yml files, managing Dependabot pull requests, configuring dependency update strategies, setting up grouped updates, monorepo patterns, multi-ecosystem groups, security update configuration, auto-triage rules, or any GitHub Advanced Security (GHAS) supply chain security topic related to Dependabot.
Generate comprehensive rollout plans with preflight checks, step-by-step deployment, verification signals, rollback procedures, and communication plans for infrastructure and application changes
Diátaxis Documentation Expert. An expert technical writer specializing in creating high-quality software documentation, guided by the principles and structure of the Diátaxis technical documentation authoring framework.
Ensure .NET/C# code meets best practices for the solution/project.
Review the C#/.NET code for design pattern implementation and suggest improvements.
.NET timezone handling guidance for C# applications. Use when working with TimeZoneInfo, DateTimeOffset, NodaTime, UTC conversion, daylight saving time, scheduling across timezones, cross-platform Windows/IANA timezone IDs, or when a .NET user needs the timezone for a city, address, region, or country and copy-paste-ready C# code.
Ready-to-use prompts for comprehensive .NET framework upgrade analysis and execution
Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.
Generates a comprehensive and best-practice-oriented .editorconfig file based on project analysis and user preferences.
Get best practices for Entity Framework Core
Create Agent Users in Microsoft Entra ID from Agent Identities, enabling AI agents to act as digital workers with user identity capabilities in Microsoft 365 and Azure environments.
Add instrumentation, build golden datasets, write eval-based tests, run them, root-cause failures, and iterate — Ensure your Python LLM application works correctly. Make sure to use this skill whenever a user is developing, testing, QA-ing, evaluating, or benchmarking a Python project that calls an LLM. Use for making sure an LLM application works correctly, catching regressions after prompt changes, fixing unexpected behavior, or validating output quality before shipping.
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Use this skill to get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using best practices.
Triage and resolve Fedora issues with dnf, systemd, and SELinux-aware guidance.
Finalize prompt file using the role of an AI agent to polish the prompt for the end user.
Detect and remove AI-generated markers from Finnish text, making it sound like a native Finnish speaker wrote it. Use when asked to "humanize", "naturalize", or "remove AI feel" from Finnish text, or when editing .md/.txt files containing Finnish content. Identifies 26 patterns (12 Finnish-specific + 14 universal) and 4 style markers.
Interactive, input-tool powered, task refinement workflow: interrogates scope, deliverables, constraints before carrying out the task; Requires the Joyride extension.
>- Build, scaffold, and deploy Power Automate cloud flows using the FlowStudio deploy a flow definition, scaffold a Power Automate workflow, construct a flow JSON, update an existing flow's actions, patch a flow definition, add actions to a flow, wire up connections, or generate a workflow definition from scratch.
>- Debug failing Power Automate cloud flows using the FlowStudio MCP server. this flow failing, inspect action outputs, find the root cause of a flow error, fix a broken Power Automate flow, diagnose a timeout, trace a DynamicOperationRequestFailure, check connector auth errors, read error details from a run, or troubleshoot
>- Connect to and operate Power Automate cloud flows via a FlowStudio MCP server. action outputs, resubmit a run, cancel a running flow, view connections, get a trigger URL, validate a definition, monitor flow health, or any task that requires talking to the Power Automate API through an MCP tool. Also use for Power Platform environment discovery and connection management. Requires a FlowStudio MCP
> Guide for using the Microsoft Fluent UI Blazor component library (Microsoft.FluentUI.AspNetCore.Components NuGet package) in Blazor applications. Use this when the user is building a Blazor app with Fluent UI components, setting up the library, using FluentUI components like FluentButton, FluentDataGrid, FluentDialog, FluentToast, FluentNavMenu, FluentTextField, FluentSelect, FluentAutocomplete, FluentDesignTheme, or any component prefixed with "Fluent". Also use when troubleshooting missing providers, JS interop issues, or theming.
Claude Skills — questions
Answers built from the skills we actually parsed.