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/rig-implement

Execute a frozen plan or bounded change, run configured gates, and produce an evidence-backed commit handoff.

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ai-rig
2948 skills16 agents2 MCP
Install
$ npx -y skills add Borda/AI-Rig --skill rig-implement --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/rig-implement

Context preview

The summary Claude sees to decide when to auto-load this skill.

Execute a frozen plan or bounded change, run configured gates, and produce an evidence-backed commit handoff.

SKILL.md

rig-implement.SKILL.md
name: Rig Implement
description: Execute a frozen plan or bounded change, run configured gates, and produce an evidence-backed commit handoff.

Rig Implement

> Read [Evidence rules](../../references/evidence.md) and [Commit handoff](../../references/commit-handoff.md).

Input

  • A frozen `plan.md` with its digest, or a bounded change with explicit scope.
  • Optional: `kind` = `feature`, `fix`, `refactor`, or `perf`.

Workflow

1. **Revalidate the plan.** Read current source and compare it with the plan's assumptions. If source contradicts the plan, stop and report; do not rewrite the plan. 2. **Start the run.** `rig_evidence` with `action: "start"`, `skill: "rig-implement"`, target paths, and the plan path. Record the plan digest. 3. **Establish a baseline.** Run the narrowest relevant test or reproduction before editing. For a refactor, capture characterization tests first. 4. **Implement in batches.** Group non-overlapping edits and their tests into one batch. Run the focused check after each batch. When a batch fails, bisect to the smallest edit so attribution is not lost. 5. **Reconcile the scope.** After the last edit and any formatter, call `rig_evidence` with `action: "refresh"` and a `message` naming what changed. This is the only way the run adopts edited source. 6. **Run configured gates.** Call `rig_gate` with `action: "run"` and the run ID. Fix failures and rerun the same gate. Never retry a failing gate unchanged, and never substitute a manual claim for a failed check. If a gate rewrites files, refresh the scope and rerun that gate. 7. **Record outputs.** `rig_evidence` with `action: "record"` for changed paths, limits, and any decision that future readers need. 8. **Finalize.** `rig_evidence` with `action: "finalize"`. A failed gate or source drift blocks completion; drift means refresh and rerun, never editing the record. 9. **Commit handoff.** Propose the exact commit message and paths. A plain commit runs when the user asked for it or a local Git grant covers it; otherwise ask once. Never push.

Rules

  • Do not touch paths outside the owned set without saying so and getting scope approval.
  • Do not delete or weaken tests to reach green.
  • Preserve unrelated working-tree changes.
  • Keep the change minimal: no opportunistic refactors outside the plan.
  • Report incomplete work as incomplete; a partial fix with a clear stop is valid.

Output

Report run ID, changed paths with digests, gate receipts, failed or skipped checks, remaining risks, and the commit handoff. Do not claim completion without a finalized run.

Read more
Ships withai-rig

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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