debug
Investigation-first debugging — gather evidence, form confirmed root-cause hypothesis, hand off to fix mode with diagnosis file.…
Review the current diff, a commit, or a path with independent read-only reviewers and a validated findings artifact.
$ npx -y skills add Borda/AI-Rig --skill rig-review --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/rig-reviewContext preview
The summary Claude sees to decide when to auto-load this skill.
Review the current diff, a commit, or a path with independent read-only reviewers and a validated findings artifact.
name: Rig Review description: Review the current diff, a commit, or a path with independent read-only reviewers and a validated findings artifact.
> Read [Evidence rules](../../references/evidence.md). This workflow is read-only; it never writes to GitHub.
1. **Classify.** `TRIVIAL`, `LOCAL`, `BROAD`, or `HIGH_RISK`. Risk categories set depth; they do not grant execution authority. 2. **Start the run.** `rig_evidence` with `action: "start"`, `skill: "rig-review"`, and the exact target paths. 3. **Collect exact source.** Record the diff and the complete bytes of every reviewed file. For `workspace`, prefer a detached review worktree so later edits cannot silently change the evidence. A digest change invalidates the review. 4. **Select axes.** `correctness` is mandatory and must be run (cannot be omitted). Add `security` for auth, credentials, deserialization, or network input; `tests` when behavior changes; `api` for public interfaces; `performance`, `docs`, and `data` when the diff warrants. Cap at four axes below `BROAD`. Also ensure coverage records what was actually inspected for correctness. 5. **Dispatch independent reviewers.** Use `rig-reviewer` (or `rig_dispatch`). Give each only the task, role card, exact source digests, and assigned axis. Reviewers are read-only and return JSON findings; the parent never counts its own reading as reviewer evidence. 6. **Validate findings.** Reject any finding without a concrete file and observed evidence. De-duplicate by signature (file + invariant), not by wording. Use `rig_findings` with `action: "write"`, the axes, the coverage, and `reviewer` naming the independent reviewer(s). That write records the review evidence bound to the scope digest. 7. **Report.** Order by severity. State the axes that ran, the axes that did not, and why. An honest partial review beats a fabricated complete one. 8. **Finalize.** `rig_evidence` with `action: "finalize"`. Open findings are a valid review outcome; they are not a completion failure. Source drift is: start a new review instead of certifying changed bytes.
Report run ID, scope digest, axes run and skipped, findings by severity, coverage limits, and confidence.
Practical agent workflows for Python, ML, and open-source maintenance. AI-Rig turns recurring work—scoping a change, reproducing a bug, reviewing a pull request, running an experiment, or checking release readiness—into explicit workflows with specialist
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