Production-grade engineering skills for AI coding agents.
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One-line summary from the repository description on GitHub
Why hot now
Star velocity +745 in Today (UTC)
About this project
Agent Skills
Production-grade engineering skills for AI coding agents.
Skills encode the workflows, quality gates, and best practices that senior engineers use when building software. These ones are packaged so AI agents follow them consistently across every phase of development.
Want fewer manual steps once the spec exists? /build auto generates the plan and implements every task in a single approved pass — you approve the plan once, then it runs autonomously. It removes the human stepping between tasks, not the verification: every task is still test-driven and committed individually, and it pauses on failures or risky steps.
Skills also activate automatically based on what you're doing — designing an API triggers api-and-interface-design, building UI triggers frontend-ui-engineering, and so on.
Quick Start
Fastest path — any agent, one command. The open skills CLI installs into 70+ agents (Claude Code, Cursor, Codex, Copilot, Cline, and more):
npx skills add addyosmani/agent-skills # install all 24 skills
npx skills add addyosmani/agent-skills --list # browse before installing
Or grab individual skills:
npx skills add addyosmani/agent-skills --skill code-review-and-quality # five-axis review before merge
npx skills add addyosmani/agent-skills --skill interview-me # requirements interrogation, one question at a time
npx skills add addyosmani/agent-skills --skill test-driven-development # red-green-refactor, enforced
Prefer a native integration? Pick your tool below.
SSH errors? The marketplace clones repos via SSH. If you don't have SSH keys set up on GitHub, either add your SSH key or use the full HTTPS URL to force HTTPS cloning during the marketplace-add step:
If /plugin install still fails with git@github.com: Permission denied (publickey) on Windows or macOS, the recommended workaround is to configure Git once to rewrite GitHub SSH URLs to HTTPS for subprocess clones:
git clone https://github.com/addyosmani/agent-skills.git
claude --plugin-dir /path/to/agent-skills
Cursor
Put workflow skills under .cursor/skills/ (sync from agent-skills/skills/) and short policies in .cursor/rules/*.mdc — do not paste full skills into rules. See docs/cursor-setup.md.
Antigravity CLI
Install as a native plugin for skills, subagents, and slash commands. See docs/antigravity-setup.md.
Use agent definitions from agents/ as Copilot personas and skill content in .github/copilot-instructions.md. See docs/copilot-setup.md.
Kiro IDE & CLI
Skills for Kiro reside under ".kiro/skills/" and can be stored under Project or Global level. Kiro also supports Agents.md. See Kiro docs at https://kiro.dev/docs/skills/
Codex
Install as a native Codex plugin (Codex CLI v0.122+):
Codex reads the root skills/ directory directly through .codex-plugin/plugin.json. Once installed, invoke skills in chat using @ (e.g., @spec-driven-development). See docs/codex-setup.md for local installation and troubleshooting.
Other Agents
Skills are plain Markdown - they work with any agent that accepts system prompts or instruction files. See docs/getting-started.md.
All 24 Skills
The commands above are entry points. The pack includes 24 skills total — 23 lifecycle skills plus the using-agent-skills meta-skill. Each skill is a structured workflow with steps, verification gates, and anti-rationalization tables. You can also reference any skill directly.
Endorsed multi-persona orchestration patterns, anti-patterns, and the "personas don't invoke personas" rule
How Skills Work
Every skill follows a consistent anatomy:
┌─────────────────────────────────────────────────┐
│ SKILL.md │
│ │
│ ┌─ Frontmatter ─────────────────────────────┐ │
│ │ name: lowercase-hyphen-name │ │
│ │ description: Guides agents through [task].│ │
│ │ Use when… │ │
│ └───────────────────────────────────────────┘ │
│ Overview → What this skill does │
│ When to Use → Triggering conditions │
│ Process → Step-by-step workflow │
│ Rationalizations → Excuses + rebuttals │
│ Red Flags → Signs something's wrong │
│ Verification → Evidence requirements │
└─────────────────────────────────────────────────┘
Key design choices:
Process, not prose. Skills are workflows agents follow, not reference docs they read. Each has steps, checkpoints, and exit criteria.
Anti-rationalization. Every skill includes a table of common excuses agents use to skip steps (e.g., "I'll add tests later") with documented counter-arguments.
Verification is non-negotiable. Every skill ends with evidence requirements - tests passing, build output, runtime data. "Seems right" is never sufficient.
Progressive disclosure. The SKILL.md is the entry point. Supporting references load only when needed, keeping token usage minimal.
AI coding agents default to the shortest path - which often means skipping specs, tests, security reviews, and the practices that make software reliable. Agent Skills gives agents structured workflows that enforce the same discipline senior engineers bring to production code.
Each skill encodes hard-won engineering judgment: when to write a spec, what to test, how to review, and when to ship. These aren't generic prompts - they're the kind of opinionated, process-driven workflows that separate production-quality work from prototype-quality work.
Skills bake in best practices from Google's engineering culture — including concepts from Software Engineering at Google and Google's engineering practices guide. You'll find Hyrum's Law in API design, the Beyonce Rule and test pyramid in testing, change sizing and review speed norms in code review, Chesterton's Fence in simplification, trunk-based development in git workflow, Shift Left and feature flags in CI/CD, and a dedicated deprecation skill treating code as a liability. These aren't abstract principles — they're embedded directly into the step-by-step workflows agents follow.
Skills should be specific (actionable steps, not vague advice), verifiable (clear exit criteria with evidence requirements), battle-tested (based on real workflows), and minimal (only what's needed to guide the agent).
