This is a structured approach to letting AI agents do the grunt work while you stay in control of quality and costs. You define evals before writing code, break work into 15-minute chunks that can be verified independently, and route tasks to Haiku for simple edits or Opus for architectural decisions. The eval-first loop is smart: run tests, capture failures, implement, then compare deltas. What's refreshing is the cost discipline section that actually tells you to track tokens and retries per task, and the review guidance that says skip style nitpicks if you already have automated formatting. If you're shipping features with AI agents instead of just using them for autocomplete, this gives you guard rails without turning into process theater.
npx -y skills add affaan-m/everything-claude-code --skill agentic-engineering --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot