A workflow for reviewing code changes, optionally against a written contract. It gathers the relevant files and rules, assigns reviewers, verifies their findings, applies fixes through delegated work, and runs a final gate.

Use it to review the current code diff or a contract-defined change, select reviewers based on the change type, check findings, and approve or reject the result with a gate.

It reduces the chance that a review misses scope, correctness, testing, or security issues. The workflow separates reporting from verification and keeps production-code edits out of the reviewer's hands.

wf-review — Skill for Claude Code by tomsej

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add tomsej/pi-ext --skill wf-review

Clone the repo

git clone --depth 1 https://github.com/tomsej/pi-ext

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tomsej/pi-ext/wf-review.svg)](https://agentmods.dev/skills/tomsej/pi-ext/wf-review)

Your own site

<a href="https://agentmods.dev/skills/tomsej/pi-ext/wf-review"><img src="https://agentmods.dev/badge/skills/tomsej/pi-ext/wf-review.svg" alt="Measured on agentmods" height="20"></a>

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 948 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00037	$0.00948
Opus 5	$0.00018	$0.00474
Sonnet 5	$0.00007	$0.00190
Haiku 4.5	$0.00004	$0.00095

Measured 8d ago against content hash 857b0d4bd4c7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

wf-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/wf-review/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/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_impact for blast radius/tests and sem_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 create or gh pr merge — for the codex harness this sentence is the only guard.

Read the full file on GitHub · 79 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

8d ago First seen · 79 lines · 37 tokens per session scan A 857b0d4bd4c7

Subscribe to this mod's changes

wf-review is a skill published in the GitHub repository tomsej/pi-ext (70 stars, last pushed 4d ago), licensed MIT. It adds 37 tokens to every session and 948 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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