Audits and improves repositories for reliable agentic work across Codex, Claude Code, and OpenCode. Reviews AGENTS.md/CLAUDE.md quality, routing, MCP, skills, and context budgets.
How this skill is triggered — by the user, by Claude, or both
Slash command
/ai-driven-development:agentic-readinessThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Default to audit-only. Present findings and wait for approval unless the user explicitly asks to implement changes.
Default to audit-only. Present findings and wait for approval unless the user explicitly asks to implement changes.
python scripts/audit_repo.py --root .
Add --include-user-scope only when the user explicitly wants personal Codex, Claude Code, and OpenCode configuration included. Never inspect credential stores or print secret values.
AGENTS.md/CLAUDE.md ownership, discovery, routing, compatibility, and CodeAlive lessons learned.Keep the report concise:
Do not penalize a repository for omitting agent-specific configuration it does not need. Do flag a claimed cross-agent setup that one of the named agents cannot discover.
When the user asks to apply changes:
AGENTS.md plus a regular CLAUDE.md containing @AGENTS.md when the same rules should serve all three agents.For more than 3,000 tracked files, emphasize navigation, bounded routing, focused verification, and retrieval support rather than copying documentation into startup context.
For a directory containing multiple child Git repositories, treat each child as an independent instruction root. Codex builds its instruction chain once per run/session, so changing a command's working directory does not load the child repository's files. Recommend an explicit meta-repository routing rule and verify each child from a fresh session or by reading its chain before the first operation.
npx claudepluginhub codealive-ai/ai-driven-development --plugin ai-driven-developmentAudit AI agent instruction files (AGENTS.override.md, AGENTS.md, configured fallbacks, CLAUDE.md, hooks, and settings) across workspaces in read-only report mode. Use when agent configs drift, rules duplicate, files go stale, or after workspace restructuring; apply fixes only when explicitly requested.
Assesses a git repository's readiness for AI coding agents using the agentready CLI, then walks through and addresses each gap.
Scores any repo across six agentic-quality dimensions (entry docs, docs health, comments, structure, enforcement, doc pairing) and maps each finding to a fix. Read-only audit.