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unclejobs-aiunclejobs-ai/second-claude-code/skills/refine/SKILL.md

refine

Skill41 starsChanged 7 days agoMITView on GitHub

Use when improving a draft until it meets a review target — the improve step after Check

42 other projects use a version of this.

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Used with

Projects with it also use addskill, apply-firmware and 10 more.

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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

Show its rules and text

We split this skill into the rules it gives an agent

18 rules. 0 are common, 7 are distinctive, and 11 are very specific to this project.

  • 0

    Common

    Most of the 37 edited versions we read keep these.

  • 7

    Distinctive

    This author's own choices. Worth a look.

  • 11

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run review-fix cycles until a draft meets a target score or verdict, with resumable state on disk.

    line 24
  2. Very specific:

    Read the current file and record a baseline hash.

    line 34
  3. Very specific:

    Run /scc:review — this MUST dispatch actual subagents per the review skill spec.

    line 35
  4. Very specific:

    After reviewers return, extract DoD-N: PASS/FAIL lines and compute per-criterion consensus (majority across reviewers).

    line 43
  5. Very specific:

    Before reverting a git-tracked file: run git diff --name-only <file>.

    line 46
  6. Very specific:

    Stop when the target is met, --max is reached, or the verdict plateaus (same verdict for 2 consecutive iterations with no severity …

    line 50
  7. Very specific:

    When called from a pipeline with input_from, the first file is the draft (--file) and the second (if present) is the initial review report …

    line 64
  8. Very specific:

    When mmbridge is detected (see references/mmbridge-integration.md) and the previous review cycle used --external, the refine skill can …

    line 84
  9. Distinctive:

    When a review finding is ambiguous or the editor needs more context before fixing:

    line 88
  10. Distinctive:

    Use this BEFORE applying fixes when a Critical or Major finding's intent is unclear

    line 95
  11. Distinctive:

    After the editor applies fixes (Step 3), before dispatching a full internal re-review (Step 4):

    line 100
  12. Distinctive:

    If resume indicates all external findings are addressed, it counts as a positive signal for the consensus gate

    line 108
  13. Very specific:

    Followup: when a review finding (especially from [external: mmbridge]) lacks actionable detail

    line 112
  14. Very specific:

    Skip both: if the original review did not use --external, or if mmbridge is not installed

    line 114
  15. Distinctive:

    Do not claim improvement without comparing verdicts between iterations.

    line 134
  16. Very specific:

    Never revert a file whose path contains ../ or resolves outside the project root.

    line 136
  17. Very specific:

    Do not simulate review inline — always dispatch through /scc:review.

    line 137
  18. Distinctive:

    Stop early if the verdict stops improving across iterations.

    line 138

“Common” is measured: kept by at least 6 in 10 of the 37 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Resolve runtime paths before file or script operations.

Iron Law

A fix without a review is not a fix.

Red Flags

  • "I fixed the wording but the meaning is basically the same" → STOP, because refinement must preserve the author's intent — changing meaning during polish is an unauthorized rewrite.
  • "The score went up so the fix must be good" → STOP, because you must compare verdicts between iterations, not just scores — a higher score with new Critical findings is a regression.
  • "Let me do one more pass, I can make it even better" → STOP, because the plateau rule (same verdict for 2 consecutive iterations) exists to prevent infinite loops — stop when improvement stalls.
  • "I'll skip the completion gate, the last review was already APPROVED" → STOP, because the final /scc:review --preset quick check is mandatory — never declare done without it.
  • "The reviewers disagreed so I'll just pick the feedback I like" → STOP, because reviewer consensus drives refinement priority — Critical and Major findings from any reviewer must be addressed before Minor ones.

Refine

Run review-fix cycles until a draft meets a target score or verdict, with resumable state on disk.

When to Use

  • A draft exists but is not good enough yet
  • The user wants a specific quality bar
  • Another skill produced output that needs iterative refinement

Workflow

  1. Read the current file and record a baseline hash. If --dod is provided, parse the semicolon-separated string into a numbered criteria list and store in state as dod_criteria.
  2. Run /scc:review — this MUST dispatch actual subagents per the review skill spec. Do NOT simulate review inline or merge reviewer perspectives into one pass. When --dod is active, inject the following block into each reviewer's context alongside any --promise text:
    ## DoD Checklist — evaluate each criterion independently
    1. [criterion text]
    2. [criterion text]
    ...
    For EACH criterion, append a line: `DoD-N: PASS` or `DoD-N: FAIL — <reason>`
    After reviewers return, extract DoD-N: PASS/FAIL lines and compute per-criterion consensus (majority across reviewers). Store results in state dod_results.
  3. Apply fixes. When --dod is active, prioritize FAIL DoD criteria first (up to 3 total including general feedback). If all DoD criteria already pass, fall back to the standard top-3 general feedback.
  4. Re-run /scc:review (with DoD checklist re-injected) and keep the new baseline only if the verdict improves; otherwise revert. If mmbridge was used in the original review, run mmbridge resume before dispatching the full re-review to get the external reviewer's preliminary assessment of fixes (see MMBridge Refinement Enhancement below). Revert strategy:
    • Before reverting a git-tracked file: run git diff --name-only <file>. If the file shows uncommitted user changes that are NOT from this refine iteration (i.e., changes that predate baseline_hash), warn the user and abort the revert unless they explicitly confirm. Never silently overwrite uncommitted work.
    • Path validation: confirm the file path resolves within the project root — reject any path containing ../ traversal or resolving outside the working directory.
    • For git-tracked files with no external uncommitted changes: use git checkout -- <file>.
    • For non-git files (e.g., in <plugin-data>): restore from baseline_content in refine-active.json.
  5. Stop when the target is met, --max is reached, or the verdict plateaus (same verdict for 2 consecutive iterations with no severity reduction). When --dod is active, the target is only considered met when all DoD criteria pass AND the score/verdict target is satisfied.
  6. Completion gate: Before declaring done, run /scc:review with --preset quick (a parameter passed to /scc:review, not a refine option) one final time (with DoD checklist if active). Only exit on APPROVED or MINOR FIXES and all DoD criteria PASS. If it returns MUST FIX or NEEDS IMPROVEMENT, or any DoD criterion is FAIL, continue refining.

Options

FlagValuesDefault
--max1-103
--targetscore (e.g., 4.5) or verdict (e.g., APPROVED)APPROVED
--promisetext injected into each reviewer's context as a constraintnone
--dodsemicolon-separated success criteria checklist (e.g. "no factual errors; every section has examples")none
--filepath to the draft to iterate onrequired
--reviewpath to initial review report (skips first review cycle)none

When called from a pipeline with input_from, the first file is the draft (--file) and the second (if present) is the initial review report (--review).

State

Data directory: Resolve <plugin-data> through the runtime path contract. Before writing state files, verify the directory exists with mkdir -p.

Save active state to <plugin-data>/state/refine-active.json with:

{"goal":"...","file":"...","current_iteration":2,"max":3,"verdicts":["NEEDS IMPROVEMENT","APPROVED"],"scores":[],"baseline_hash":"...","baseline_content":null,"is_git_tracked":true,"feedback_log":[],"dod_criteria":["no factual errors","every section has examples"],"dod_results":[[true,false],[true,true]]}
  • dod_criteria: array of criterion strings parsed from --dod. Empty array when --dod is not used.
  • dod_results: array of arrays — one boolean array per iteration, positionally matching dod_criteria. true = PASS (majority of reviewers agreed), false = FAIL.
  • baseline_content: stores the full file content when is_git_tracked is false (non-git files cannot be reverted via git checkout)
  • is_git_tracked: set at step 1 by running git ls-files --error-unmatch <file>. Determines the revert strategy.

MMBridge Refinement Enhancement

When mmbridge is detected (see references/mmbridge-integration.md) and the previous review cycle used --external, the refine skill can leverage mmbridge's session continuity for smarter iterations.

Followup — Clarifying Review Findings

When a review finding is ambiguous or the editor needs more context before fixing:

mmbridge followup --tool kimi --prompt "<specific question about a finding>" --latest --json > /tmp/mmbridge-followup-${RUN_ID}.json
  • --latest: reuses the most recent review session for this project
  • Use this BEFORE applying fixes when a Critical or Major finding's intent is unclear
  • Parse the followup JSON response and provide it to the editor alongside the original finding

Resume — Re-review After Fixes

After the editor applies fixes (Step 3), before dispatching a full internal re-review (Step 4):

mmbridge resume --action followup -y --json > /tmp/mmbridge-resume-${RUN_ID}.json
  • This asks the original external reviewer to evaluate the fixes against its earlier findings
  • The resume result is merged as supplemental context into the next /scc:review cycle
  • If resume indicates all external findings are addressed, it counts as a positive signal for the consensus gate

When to Use

  • Followup: when a review finding (especially from [external: mmbridge]) lacks actionable detail
  • Resume: at every re-review cycle if mmbridge was used in the original review
  • Skip both: if the original review did not use --external, or if mmbridge is not installed

Cost Note

Followup and resume reuse existing mmbridge sessions — they are cheaper than dispatching a full new review.

Output

Return the final draft plus an iteration log showing verdict progression and major changes. When --dod is active, append DoD status per iteration:

Round 0 (baseline):  2.0/5  ||||..............  MUST FIX
  DoD: [x] no factual errors  [ ] every section has examples

Round 1 (post-edit): 3.8/5  |||||||||||||||...  MINOR FIXES  (+1.8)
  DoD: [x] no factual errors  [x] every section has examples  ✓ ALL PASS

Gotchas

  • Do not claim improvement without comparing verdicts between iterations.
  • Revert through git checkout -- <file> for git-tracked files, or restore from baseline_content for non-git files. Never rely on memory alone. Always check git diff --name-only <file> before reverting — abort with a warning if uncommitted user changes are detected outside this refine pass's own edits.
  • Never revert a file whose path contains ../ or resolves outside the project root.
  • Do not simulate review inline — always dispatch through /scc:review.
  • Stop early if the verdict stops improving across iterations.
  • The completion gate is mandatory — never skip the final /scc:review --preset quick check.

Subagents

reviewer: { skill: /scc:review, constraint: "return score plus ranked feedback" }
editor: { model: opus, tools: [Read, Edit], constraint: "apply only the top 3 feedback items" }

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