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Ra1 report

Skill tjboudreaux/ready-agent-1/skills/ra1-report

Ready Agent 1 — is your codebase ready for the agents? Score agent-readiness (deterministic, cited, Level 1-5) and clear the gates.

Install
npx -y skills add tjboudreaux/ready-agent-1 --skill ra1-report

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  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

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Ready Agent 1 scans your repo for agent-readiness — a deterministic, cited score (Level 1–5 across Style & Validation, Build System, Testing, Documentation, Dev Environment, Security, and Task Discovery) plus advisory guidance. Use when the user asks to assess agent readiness, score a repo, check whether a codebase is ready for AI agents, run Ready Agent 1, generate a readiness report, or find out a repo's readiness level. Runs a local pure-stdlib engine; the score is reproducible and the agent only adds non-gating advisory.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

5.7 KB, as published. Nobody here has run it

Agent Readiness Report

Produce a trustworthy readiness report for a repository. The deterministic engine owns the score; you (the agent) add advisory commentary only. You must never change the engine's score.

Steps

  1. Run the engine (it does all the deterministic work — file/config parsing, git history, and, if gh is authenticated, the GitHub API). Mirroring Droid's /readiness-report, require an origin remote and persist local history:

    python3 "$(dirname "$0")/scripts/readiness/cli.py" report \
      --project <repo-path> --format json,markdown \
      --require-origin --store-history --out <repo-path>/.agents/readiness
    

    This requires a git repo with an origin remote (drop --require-origin to scan an arbitrary local path — an RA1 extension). It writes report.md, report.json, and the canonical latest.json under .agents/readiness/, plus an immutable timestamped snapshot and index under .agents/readiness/history/<identity_hash>/, and prints the canonical JSON. The report carries a redacted repository identity (no remote credentials, no absolute paths). Read the prior latest.json first, if present, to compute a Δ vs last run (only when the schema, engine, registry, and detector versions match; otherwise skip the delta).

  2. Emit the score verbatim. Your final report MUST contain a fenced ```json block holding the engine's score object exactlylevel, level_name, pass_rate, gating_passed, gating_total, pillars. Do not change a single number. This is the authoritative, reproducible score.

  3. Add the human summary from the engine's markdown (Level, Applications, per-pillar criteria with their statuses and cited evidence, Action Items).

  4. Add a ## T4 Advisory section (qualitative, non-gating). The engine deliberately leaves these soft judgments to you; label each clearly as advisory opinion grounded strictly in engine findings and files you actually read. Use one labelled sub-heading per registered judgment id:

    • Naming Consistency (naming_consistency)
    • Code Modularization (code_modularization)
    • N+1 Query Avoidance (n_plus_one_query)
    • README Quality (readme_quality)
    • AGENTS.md Quality (agents_md_quality)
    • Service-Flow Documentation Quality (service_flow_doc_quality)
    • Runbook Quality (runbooks_quality)
    • PII Handling (pii_handling)
    • Privacy Compliance (privacy_compliance)
    • User Feedback Loop (user_feedback_loop) — judged question: "Is there evidence user/customer feedback reaches prioritization — feedback issue templates or categories, triage labels in use, product metrics beside technical metrics, or documented feedback→backlog flow?"
    • Verification-loop (AC/DC) maturity — map engine findings onto Guide (docs.agents_md*, docs.agent_verify_contract, docs.architecture_doc), inner-loop Verify (build.check_command, devenv.agent_hooks), outer-loop Verify (build.ci_runs_tests, testing.coverage_threshold, testing.new_code_quality_gate, security.branch_protection), and Solve (style.precommit_hooks, ra1-fix). Name the single highest-leverage missing stage. When a stage fails, point to the acdc config block and templates/acdc/ pack as the remediation path; keep this mapping advisory and never alter the engine score. For each, cite the specific file/finding, explain why it matters, and give the highest-leverage next step. Example (good): "AGENTS.md quality (advisory): the build section names make test but the repo uses pytest (see AGENTS.md L12 vs pyproject) — align them so an agent picks the right command." Note stale or low-quality docs the engine can only see as "present".

Contract (do not violate)

  • Never claim a higher Level than the engine reports. The fenced score block is the source of truth.
  • Never mark a failing criterion as passing. If the engine says fail/unknown, your prose must agree.
  • Never invent criteria, evidence, or passing results. Cite only what the engine surfaced or files you actually read.
  • Never claim autonomy clearance. Do not describe the repo as ready for unattended/autonomous operation unless the engine reports Level 5 (Autonomous); T4 commentary is advice, not clearance.
  • Do not assert that a specific criterion is "gating" or "non-gating" — only the engine's data says so. Don't add caveats absent from the findings.
  • T4 advisory is opinion and is explicitly non-gating — it cannot move the Level, GitHub annotations, JUnit, or SARIF.

Notes

  • If the engine reports project_type: unknown, surface that honestly — type-dependent criteria are unknown, not silently skipped. Suggest the user pin the type via .agents/readiness/config.json.
  • T2 (GitHub) criteria are skipped when gh is unavailable; recommend authenticating gh for a fuller score.
  • To raise the score, hand off to the ra1-fix skill (the Loadout).

Keep looking

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