tomsej/pi-ext/wf-review
Claude Code and agent skill by tomsej/pi-ext
- community
Checking that the SKILL.md file is still in the repository.
Review a change with an optional workflow contract using deterministic scope, adaptive cross-model reviewers, verified findings, fixes, and a gate. Use standalone or from wf-impl.
Install
npx vskill@latest install tomsej/pi-ext/wf-reviewSKILL.md
/wf-review
Argument: optional absolute path to a contract. Without a contract, review the current diff. You own the review: reviewers only report; verify every finding and delegate fixes sequentially. Never edit production code yourself.
GATE = node ~/Workspace/pi-ext/wf/wf-gate.mjs
1. Scope
TARGET = sc worktree status --json → target_branch (fallback main). Run ocr delegate preview --from TARGET --to HEAD, restore excluded product files such as .md when they carry the change or the contract names them, then load rules with ocr delegate rule <files>. Keep lockfiles and generated code out.
Write .wf/review-packet.md: contract path or “no contract”, refs, merge_base, final files, diff stats, and rules. Every reviewer gets it. Without ocr, use git diff --stat TARGET...HEAD and disclose the fallback.
2. Pick the panel
With a contract, use its exact GATE agents <spec> --json → review plan; never infer models from YAML. Without a contract, inspect the packet and use:
- docs/tests-only with no runtime behavior or sensitive config: 1 reviewer;
- behavior changes: 2 reviewers for correctness and tests/edge cases;
- security, auth, permissions, secrets, migrations, data integrity, concurrency,
public APIs, or a large cross-module diff: 3 reviewers for correctness, the relevant risk, and impact/tests.
Read PI_PROVIDER and PI_MODEL. Reviewers must differ by model from the current session and each other. Prefer claude/fable, codex/gpt-5.6-sol, pi/zai/glm-5.2, then pi/anthropic/claude-opus-5. Skip matching or unavailable models, record the fallback, and never add reviewers merely because more models exist.
3. Review — max 2 rounds
Run each round's reviewers IN PARALLEL with subagent_spawn, each in a fresh context; never collapse them onto one model. Give each the packet, focus, read-only mode, and these rules:
- with claude harness: the prompt MUST start with
/code-review; codex would
treat /review as plain text, so other harnesses get no slash prefix;
- with pi harness: use
sem_impactfor blast radius/tests andsem_context; - findings are CLAIMS: severity,
file:line, problem, and impact; with a
contract also cite the violated criterion or scope;
- Critical/High = bug, security, data loss, or uncovered criterion; Medium =
performance or missing error handling with context; discard Low unless useful;
- project rules are the checklist; read-only means never
gh pr createor
gh pr merge — for the codex harness this sentence is the only guard.
Save raw outputs to .wf/reviews/<HEAD>/round-<N>/<focus>.md; a missing planned report means incomplete review. Verify every finding against the code and explain rejections. Batch legitimate findings by 3–5 and delegate them sequentially; only one agent may edit at a time. Each batch ends with a commit and targeted test. Send repeatable mechanical findings to review-guards; never edit skills, the workflow pipeline, or AGENTS.md yourself.
Run round 2 only after fixes and only on changed areas. With a contract use its planned round; standalone use one best-matching reviewer.
4. Result
With a contract, GATE verify <spec> quick must pass (max 3 repair attempts per hypothesis). Without a contract, do not run GATE agents or verify; after fixes run targeted project tests. An unresolved finding or missing report means FAILED; otherwise PASS. wf-impl creates the review attest only after its final full gate; never create it here.
Report fixes with commits, rejections with reasons, planned/used reviewers and model fallbacks, artifact paths, scope stats, and gate/test results.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/wf-review/SKILL.md
Popularity
- Repository stars
- 78
- Repository forks
- 6
- 7-day trend score
- 22
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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