Addy Osmani (Google Chrome engineering lead) packaged senior engineering practices into 24 skills that AI coding agents can follow. The insight: AI agents naturally take shortcuts — skipping specs, tests, and security reviews. These skills enforce the discipline that experienced engineers bring to every project. Its rapid GitHub adoption has made it a reference implementation for encoding engineering culture into agent workflows.
Source: GitHub - addyosmani/agent-skills
The 8 Slash Commands
Each command maps to a phase of the software development lifecycle:
| Command | Phase | What It Does |
|---|---|---|
/spec |
Define | Spec before code — clarify requirements first |
/plan |
Plan | Break work into small, atomic tasks |
/build |
Build | Implement one slice at a time |
/test |
Verify | Tests are proof, not decoration |
/review |
Review | Improve code health before merge |
/webperf |
Verify | Measure web performance before optimizing |
/code-simplify |
Simplify | Clarity over cleverness |
/ship |
Ship | Faster is safer — deploy to production |
Six Development Phases, 24 Skills
Phase 1: DEFINE
├── interview-me
├── idea-refine
└── spec-driven-development
Phase 2: PLAN
└── planning-and-task-breakdown
Phase 3: BUILD
├── incremental-implementation
├── test-driven-development
├── frontend-ui-engineering
├── api-and-interface-design
├── context-engineering
├── source-driven-development
└── doubt-driven-development
Phase 4: VERIFY
├── browser-testing-with-devtools
└── debugging-and-error-recovery
Phase 5: REVIEW
├── code-review-and-quality
├── code-simplification
├── security-and-hardening
└── performance-optimization
Phase 6: SHIP
├── git-workflow-and-versioning
├── ci-cd-and-automation
├── deprecation-and-migration
├── documentation-and-adrs
├── observability-and-instrumentation
└── shipping-and-launch
Plus a using-agent-skills meta-skill, 4 specialist agent personas, and 7 reference checklists.
What Makes These Skills Special
Each SKILL.md follows a standardized structure with an “anti-rationalization table” — anticipating shortcuts agents try to take:
| Agent Excuse | Skill Response |
|---|---|
| “I’ll add tests later” | Tests are proof. No proof = not done. |
| “This is just a small change” | Small changes cause big outages. |
| “Seems right” | Seems is not evidence. Run it. |
| “I don’t need a spec for this” | You don’t know what you’re building without one. |
Google Engineering Culture Encoded
The skills draw heavily from Software Engineering at Google:
- Hyrum’s Law in API design — backward compatibility matters
- The Beyonce Rule in testing — “If you liked it, you should’ve put a test on it”
- Chesterton’s Fence in code simplification — don’t remove what you don’t understand
- Change sizing norms (~100 lines) in code review
- Trunk-based development in git workflow
- Shift Left principle in CI/CD — catch problems early
Installation
# Claude Code
/plugin marketplace add addyosmani/agent-skills
/plugin install agent-skills@addy-agent-skills
# Gemini CLI
gemini skills install https://github.com/addyosmani/agent-skills.git --path skills
# Cursor / Windsurf / Copilot
# Follow the repo's tool-specific setup docs for rules, agent definitions, or instructions files.
# Manual (any agent)
git clone https://github.com/addyosmani/agent-skills.git
Skills are plain Markdown — any agent accepting system prompts can use them.
How LearnAI Team Could Use This
- Teaching software engineering — the 6-phase lifecycle is a pedagogical framework itself
- Improving AI-assisted student projects — install the skills to enforce best practices
- Studying skill design patterns — the anti-rationalization table is a novel concept worth teaching
- Building custom skills — use this repo as a template for encoding domain expertise
Real-World Use Cases
- Engineering teams — enforce consistent practices across all AI-assisted development
- Open source projects — standardize contribution quality regardless of agent used
- Junior developers — learn senior-level practices by reading the skill files
- Code review — the reviewer agent persona provides structured, opinionated feedback