If you're building or debugging AI agents and frustrated by low completion rates or endless retry loops, this is the checklist you need. It covers the four constraint areas that actually matter: action space design, observation formatting, error recovery, and context budgeting. The guidance is opinionated and specific, like using micro-tools for risky operations and always including next_actions in tool responses. It also pushes a hybrid ReAct plus function-calling pattern as the sweet spot for most workflows. Honestly, this reads like hard-won lessons from someone who's shipped agents in production and watched them fail in predictable ways.
npx -y skills add affaan-m/everything-claude-code --skill agent-harness-construction --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot