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Found 11,851 Skills
Continuous Agentation annotation handling. Use when the user says "watch mode", asks you to watch for Agentation annotations, process feedback as it arrives, or keep fixing annotation-driven changes until told to stop or a timeout is reached.
Framework-agnostic persistent memory and self-improvement loops for AI agents. Scaffolds shared state, task queues, and learnings files that can be read/written by Claude, Gemini, and Antigravity. Use this to initialize an Agentic OS layer in any workspace and instruct agents on how to use it.
Orchestrate multi-agent AI workflows with ultrawork, discipline agents, team mode, and hash-anchored editing for autonomous code development
Native web workspace for Hermes Agent with chat, terminal, memory, skills, inspector, and multi-agent orchestration
TypeScript-native multi-agent orchestration framework that decomposes goals into task DAGs automatically with MCP and live tracing
A minimal teaching framework for understanding AI Agent architecture with core loop, fake LLM interface, and skill discovery system
Disciplined spec-driven test-driven development workflow for building software with AI coding agents. Transforms ambiguous requests into verified implementations through structured specification, test derivation, and strict TDD. Handles greenfield projects, brownfield enhancements (with or without existing tests), refactors, and complex bug fixes with workflow-specific guidance for each. Use when the user requests a new feature, module, enhancement, refactor, API, data pipeline, CLI tool, or system with multiple requirements, edge cases, or unclear specifications. Also use for complex bug fixes requiring root cause analysis. Triggers on phrases like "add a feature", "implement", "build a new module", "build an API", "build a CLI", "build a data pipeline", "refactor", "fix this bug", "write tests for", "TDD", "test-first", "the requirements are unclear", "characterization tests", or "spec this out". Triggers when modifying code with adjacent test files (`tests/`, `*_test.py`, `*.test.ts`, `*.spec.ts`, `spec/`, `__tests__/`) or test framework config (pytest.ini, jest.config.*, go.mod with testing imports, Cargo.toml with [dev-dependencies], package.json with a test script). Triggers when the user mentions edge cases, invariants, acceptance criteria, EARS notation, or red-green-refactor. Do NOT use for simple one-line fixes, cosmetic changes, formatting, renames, dependency bumps, or tasks where requirements are already fully specified with tests provided.
Systematic documentation authoring workflow for AI coding agents. Analyzes repositories to determine what documentation is needed, classifies each document by Diataxis type (tutorial, how-to, reference, explanation), and generates accurate, maintainable documentation that stays synchronized with the codebase. Handles greenfield projects (no docs exist), brownfield updates (refresh, enhance, rewrite existing docs), and doc audits with workflow-specific guidance for each. Use when the user requests documentation for a project: README creation, API reference, architecture docs, developer guides, changelogs, or any technical writing tied to a codebase. Also use when existing docs need auditing, updating, rewriting, or restructuring. Triggers on phrases like "write a README", "document this project", "API reference", "architecture doc", "developer guide", "getting started guide", "tutorial", "how-to", "audit our docs", "what docs are missing", "refresh the docs", "Diataxis", "doc the public API", "write a CHANGELOG", "explain this codebase", "onboarding doc", or "ADR". Triggers when creating or editing `README.md`, `CONTRIBUTING.md`, `CHANGELOG.md`, `docs/`, `mkdocs.yml`, `docusaurus.config.*`, `sphinx`/`conf.py`, ADRs, or any markdown file paired with code. Triggers when public APIs, CLI flags, configuration options, or environment variables change and the user wants the docs kept in sync. Do NOT use for standalone prose, marketing copy, blog posts, design documents, RFCs unrelated to a codebase, or documents where the source of truth is not source code.
Systematic GitHub Actions workflow authoring skill for AI coding agents. Analyzes repositories to determine project type, language ecosystem, and deployment targets, then generates production-grade CI/CD workflows with proper security hardening, caching, and optimization. Handles greenfield projects (no workflows exist), brownfield updates (modify, optimize, secure existing workflows), and workflow audits with workflow-specific guidance for each. Use when the user requests GitHub Actions workflows: CI pipelines, CD deployments, release automation, scheduled jobs, or any .github/workflows YAML authoring. Also use when existing workflows need auditing, optimizing, securing, or restructuring. Triggers on phrases like "set up CI", "add CI/CD", "GitHub Actions workflow", "release automation", "deploy on tag", "publish to npm/PyPI", "schedule a job", "cron workflow", "matrix build", "workflow.yml", "actions/checkout", "permissions", "harden this pipeline", "pin actions to SHA", "OIDC", "least privilege", "supply-chain", "audit my workflows", "speed up CI", or "cache dependencies". Triggers when creating or editing files under `.github/workflows/`, `action.yml`/`action.yaml` (composite or Docker actions), or `.github/dependabot.yml`. Triggers when the user mentions migrating from GitLab CI, CircleCI, Travis, Jenkins, Drone, or Buildkite to GitHub Actions. Do NOT use for non-GitHub CI systems (GitLab CI, CircleCI, Jenkins) unless the user is migrating TO GitHub Actions. Do NOT use for general bash scripting, Makefiles, or local-only build configuration.
Curated collection of 1000+ agent skills compatible with Claude Code, Codex, Gemini CLI, Cursor, and more
使用 agency-agents-zh 中文 AI 智能体角色库，为 AI 编程工具提供 215 个即插即用的专家角色
Hermes-native AIOps agent for evidence-driven incident response, approval-gated remediation, and runbook learning