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. 79 341 files from 1 736 authors, of which 61 700 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.
>- Behavioral rules and lifecycle event handlers for the dev-tools package. Defines automated behaviors that trigger at specific points in the agent workflow. (converted from hooks)
>- Captures project-specific patterns and anti-patterns into the project's CLAUDE.md. Loaded by other skills (bug-killer, feature-dev, etc.) when they discover project-specific knowledge worth encoding for future sessions.
Prepare and execute a Python package release with verification steps. Use for releasing Python packages with uv and ruff.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
Session-start lifecycle hooks for cross-plugin dependency resolution. Creates symlinks so cross-package references work in cached plugin environments.
Prepare and execute a Python package release with verification steps. Use for releasing Python packages with uv and ruff.
>- Systematic, hypothesis-driven debugging workflow with triage-based track routing. Use when asked to "fix this bug", "debug this", "why is this failing", "this is broken", "investigate this error", "track down this issue", or any debugging situation. Supports --deep flag to force full investigation.
Provides architectural pattern knowledge for designing feature implementations including MVC, event-driven, microservices, and CQRS patterns. Use when designing system architecture or choosing implementation patterns.
Provides code quality principles including SOLID, DRY, testing strategies, and best practices for implementation review. Use when reviewing code or applying quality standards.
Keep a Changelog format guidelines and entry writing best practices. Use when writing changelog entries, updating CHANGELOG.md, or following Keep a Changelog specification.
Produce a structured codebase analysis report with architecture overview, critical files, patterns, and actionable recommendations. Use when asked to "analyze codebase", "explore codebase", "understand this codebase", "map the codebase", "give me an overview of this project", "what does this codebase do", "codebase report", "project analysis", "audit this codebase", or "how is this project structured".
Deep exploration and synthesis workflow using agent teams with dynamic planning and hub-and-spoke coordination. Use when asked for "deep analysis", "deep understanding", "analyze codebase", "explore and analyze", or "investigate codebase".
>- Documentation management workflow for MkDocs sites and standalone markdown files — initialize, generate, update docs, and create change summaries. Use when asked to "create docs", "write README", "update documentation", "generate docs site", "write CONTRIBUTING", "manage documentation", or "docs changelog".
>- Generate a markdown report documenting codebase changes from the current session — files added, modified, deleted, and a summary of what was done. Use when asked to "document changes", "generate change report", "save changes report", "what did I change", "session report", "summarize my changes", or "write a changes report".
Commit staged changes with conventional commit message. Use when user says "commit changes", "commit this", "save my changes", or wants to create a git commit.
Feature development workflow with exploration, architecture, implementation, and review phases. Use for implementing new features or significant changes.
Provides language-specific patterns for TypeScript, Python, and React including idioms, best practices, and common patterns. Use when implementing features in these languages.
Guides discovery and application of project-specific conventions including code patterns, naming, structure, and team practices. Use when exploring a codebase or implementing features to match existing patterns.
>- Captures project-specific patterns and anti-patterns into the project's configuration file. Loaded by other skills (bug-killer, feature-dev, etc.) when they discover project-specific knowledge worth encoding for future sessions.
>- Provides Mermaid diagram syntax, best practices, and styling rules for technical visualizations. Use when creating diagrams, flowcharts, sequence diagrams, class diagrams, state diagrams, ER diagrams, architecture diagrams, C4 diagrams, visualizations, or any visual documentation in markdown. Always use this skill when generating or updating Mermaid code blocks.
Behavioral rules and lifecycle event handlers for the core-tools package. Includes auto-approval of file operations targeting deep-analysis session directories.
General-purpose LinkedIn automation – fetch profiles, search people and companies, send messages, manage connections, create posts, and more. Use when the user wants to interact with LinkedIn.
Two-phase LinkedIn lead pipeline driven by linkedin-cli. Phase A imports leads from a search URL or filters, qualifies them against a configurable ICP via sub-agent, and stores them in a local SQLite database with round-robin assignment across one or more LinkedIn accounts. Phase B runs on a schedule per account — sends connection invites up to a daily limit and withdraws stale pending requests. Use when the user wants to grow their network from LinkedIn searches, manage outgoing invites at scale, ask status questions (counts, conversion, pending older than N days, last imports), pause/resume an account, change ICP, or install the recurring scheduler.
Batch-scan workspace Flutter/Android/iOS/Node.js projects, report cache usage, and perform tiered cleanup to free disk space. Triggers when the user says "clean cache", "disk space low", "free up space", or similar.
Use when reviewing code changes — MR/PR review, local commits, or uncommitted changes. Reviews document compliance, content quality (architecture soundness, test completeness, observability coverage), and end-to-end consistency (User Story ↔ design ↔ code ↔ tests ↔ observability). Triggers on "review MR", "review this commit", "review my changes", "code review", "help me review".
Quickly create a CI Pipeline for embedded repositories (SonarQube incremental C-language scanning). Triggers when the user says "add a Pipeline to this repo", "create CI configuration", "integrate SonarQube", "embedded project needs a Pipeline", or when a repo has no .gitlab-ci.yml and cannot merge MRs.
Create and review .gitlab-ci.yml files based on GitLab CI best practices and company standards. Use when creating CI/CD pipelines for new projects, reviewing existing .gitlab-ci.yml, or optimizing pipeline configuration.
Write documents using the HWPR/AWOR framework -- separating human value judgments from AI-expanded content so critical information is not buried. Triggers when the user requests writing, rewriting, or reviewing document quality.
Use when designing a new feature or system, making architecture decisions, writing technical design docs, or structuring project documentation. Triggers on "design", "architecture", "technical design", "ADR", "system decomposition", "how should I structure this", "设计方案", "架构设计", "技术方案", "文档体系", "写 User Story", "写文档". Also use when reviewing existing architecture docs or asking "where should I put this doc?
Standard R&D process orchestrator — guides the full development lifecycle from User Story to CD. Invoke when user says "start a new feature", "new requirement", "我要开发一个新功能", "开始需求", "next step?", "研发流程", or resumes work on an existing feature. Also invoke proactively when any non-trivial feature work begins, even if the user just says "let's build X". Do NOT invoke for one-off bug fixes, hotpatches, or purely exploratory tasks with no deliverable.
Cross-platform code submission workflow - Lint check, non-destructive review, manual verification document, smart staging, clean commit, MR creation. Auto-detects project type (Android/iOS/backend) and adapts to the corresponding lint/build tools. Triggers when the user says "submit code", "prepare to submit", "submit", "start submission flow", or "code submit".
Create and manage GitLab Merge Requests on gitlab.example.com repositories, driving them to a truly mergeable state. Automatically generates User Story documentation, constructs MR descriptions (with blob links), pushes and creates MRs, polls CI pipeline status via API and fixes failures, resolves merge conflicts, and loops until all MR checks pass with no conflicts. Triggers when the user says "submit MR", "create MR", "push and create MR", "merge to main", or needs to submit the current branch for review.
Query and manage Grafana dashboards, alert rules, and data sources via HTTP API. Use when viewing dashboards, troubleshooting alerts, checking service metrics, finding data sources, or when Grafana, monitoring, alerts, dashboards, or observability is mentioned.
Check SKILL.md files for security risks including prompt injection, hardcoded secrets, and compliance with security best practices. Use when creating or reviewing Skills in the your skills repository.
Perform a structured security and compliance review using evidence from code/config/docs. Use for MR/PR review, architecture review, and periodic full scans. Detects secrets exposure, PII leakage, access control gaps, and compliance violations.
Mock Engine local development environment management. Use for starting/stopping mock services, loading test data, creating test scenarios, and troubleshooting startup issues. Triggers when the user mentions "start mock", "mock environment", "local dev environment", "mock-up", "test data", or "test scenarios".
Query Prometheus monitoring metrics and alert rules. Use when the user needs to check CPU/memory/disk utilization, service health, audit alert rules, analyze capacity trends, or mentions Prometheus, PromQL, metrics monitoring, or targets.
Design and implementation guide for parallel multi-worktree development environments. Use whenever the user mentions multi-worktree development, git worktree, port conflicts, concurrent dev environments, feature branch isolation, local environment setup, or multi-developer collaboration conflicts. Even if the user casually says "we have several worktrees running simultaneously", this Skill should be triggered to guide them toward a proper layered environment.
Manage Kubernetes cluster resources via kubectl. Use when user needs to view, troubleshoot, or modify K8s workloads across multiple clusters.
Create and configure Sentry projects across staging/production environments via REST API. Use when user needs to onboard a new service to Sentry, create Sentry projects, or set up error monitoring for a new application.
>- Use when the user says "oncall", "check alerts", "start oncall", "patrol", "health check", "retrospective", "iterate", "improve sre-agent", or provides PagerDuty alert content, or asks to query/acknowledge/resolve PagerDuty incidents. Should also trigger even if the user just says "check what alerts are there", "run a patrol", or "ack this alert".
Professional User Story and documentation system construction. Assists in writing high-quality User Story documents through guided interviews to uncover requirements context and acceptance criteria, and places documents precisely in the standardized docs directory structure. Triggers when the user requests writing User Stories, describing feature requirements, or initializing project documentation structure.
Audit Terraform codebases for security, cost, code quality, and architecture issues. Use when reviewing Terraform projects, checking infrastructure-as-code compliance, or assessing AWS resource configurations for best practices.
Query Sentry errors, triage issues, and check release health via REST API. Use when debugging exceptions, investigating crash reports, triaging error issues, checking release stability, or any error monitoring and issue tracking task. Also triggers on mentions of Sentry, errors, exceptions, crashes, stack traces, or error rates.
Perform local secret scanning, remote repository scanning, pre-commit integration, and single-credential verification using TruffleHog CLI. Triggers when the user mentions trufflehog, secret scan, leaked credential investigation, Git history scan, remote repo scan, pre-commit, or post-rotation credential verification.
Universal layered testing strategy — generate a complete test plan, layered architecture, and execution plan based on project type (Backend+APP / Backend+WEB / Backend+APP+Embedded)
Discover missing UAT test scenarios from the user's perspective, confirm requirements through guided interviews, and output user story files in story-craftsman template + Gherkin Given/When/Then format. Use when the user mentions "add test cases", "missing tests for XX scenario", "write UAT cases", "write test scenarios", "brainstorm test cases", or discovers test coverage gaps. Should also trigger even if the user just mentions a feature "hasn't been tested for XX situation".
VOC (Voice of Customer) analysis and competitive intelligence research. Collects user feedback from Reddit, Twitter, Amazon, App Store, YouTube, Facebook Groups, Discord, and other platforms via Apify Agent Skills and Web Search, performs semantic tagging, pain point mining, sentiment analysis, and competitive comparison, and generates data-driven market insight reports. Triggers when the user mentions VOC analysis, user feedback analysis, market research, competitive analysis, product review analysis, pain point analysis, customer feedback, competitive intelligence, customer sentiment, review analysis, or needs to collect and analyze user voices from multiple platforms. Should also trigger even if the user just says "check how users rate this product" or "analyze competitors".
Use this skill when the user is building with `xsai` or any `@xsai/*` package, or is evaluating xsAI for a small OpenAI-compatible workflow with text generation, streaming, tool calling, structured output, embeddings, image generation, speech synthesis, or transcription.
| Analyze source code and produce an enterprise-quality, domain-organized Wiki under `.nium-wiki/`.
INVOKE THIS SKILL when auditing an AI agent or LLM app for regulatory compliance. Covers EU AI Act, GPAI Code of Practice, GDPR, NIST AI RMF, Colorado AI Act, HIPAA, and ISO 42001. Scans the codebase for compliance gaps, cross-references Arize instrumentation for audit trail coverage, and produces an actionable remediation checklist tailored to the selected frameworks.
Handles LLM-as-judge and code evaluator workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, code evaluator, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.
Manages Arize users, organizations, spaces, projects, roles, role bindings, resource restrictions, and API keys via the ax CLI. Use for enterprise admin workflows: inviting and offboarding users, onboarding new teams, creating custom roles for SAML/SSO mappings, assigning roles to users, restricting project-level access, and managing service keys for multi-tenant architectures. Covers ax users, ax organizations, ax spaces, ax projects, ax roles, ax role-bindings, and ax api-keys.
Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.
Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.
Adds Arize AX tracing to an LLM application for the first time. Detects the stack, routes to the single matching integration doc, wires auto-instrumentation after user confirmation, and verifies traces land. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.
Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.
Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.
Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.
INVOKE THIS SKILL for Arize Prompt Hub and `ax prompts` workflows: author or import templates and save (Workflows A–B), label/promote (C), or list/get/edit/delete/duplicate (D). Use when the user mentions ax prompts, Prompt Hub, creating/editing/saving a prompt, `{variable}` placeholders, or production/staging labels. For improving prompt text using traces or eval scores, use arize-prompt-optimization. For running experiments, use arize-experiment.
Claude Skills — questions
Answers built from the skills we actually parsed.