review-work

A code-review process that uses separate AI reviewers to inspect uncommitted changes. It divides the changed files by area and asks reviewers to look for bugs, rule violations, and design problems.

In plain words
What is it for?
Use it to review the current Git diff, run relevant tests, check project rules, and examine architecture when a change is broad or risky.
Why use it?
A single review can miss issues, especially when a change affects several parts of a project. Independent reviewers provide different checks before the changes are committed.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/peterkrueck/claude-code-development-kit/review-work
Any agent
npx skills add peterkrueck/Claude-Code-Development-Kit --skill review-work
Clone the repo
git clone --depth 1 https://github.com/peterkrueck/Claude-Code-Development-Kit

Made for: Claude Code, Codex.

Per session 143 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,961 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00143 $0.02961
Opus 5 $0.00072 $0.01481
Sonnet 5 $0.00029 $0.00592
Haiku 4.5 $0.00014 $0.00296

Measured 3d ago against content hash c0a122dd0f1e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

review-work 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 3d 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/review-work/SKILL.md · 280 lines

How it starts

The opening of the file, as written. The whole thing — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Work — Automated Code Review

Review uncommitted code changes using Claude sub-agents as independent reviewers. The invoking agent (you) triages the diff and decides who reviews; reviewers self-prime via /prime, verify API/library claims via Context7, and report against progress.md intent.

This skill is run by an AI, not by a human — use judgment about the change you just made. Don't apply a fixed rubric mechanically. Zero external dependencies: reviewers are Claude sub-agents.

Process

Step 1: Capture the Diff (+ Tests)

Run these and save the output:

git diff --stat HEAD
git diff HEAD

git diff HEAD captures uncommitted work — the normal pre-commit flow. If the work was already committed (e.g. direct-to-main), review the last commit instead: git diff HEAD~1 HEAD (or git show HEAD).

If the project has a test command configured and relevant source changed, run it and capture the output:

# Use whatever test/build command is appropriate for this project's stack.
# e.g. npm test · pytest · cargo test · go test ./... · the test_command in
# hooks/config/pipeline.json if set.

Test/build failures are the #1 finding for every reviewer — include the failure output in each reviewer's prompt verbatim.

Step 2: Triage

Look at the changed file paths and produce two lists.

Impacted modules — by default the whole project is one scope (one project per repo). Only split into modules/components when the diff clearly spans distinct top-level areas (e.g. api/ vs web/, backend/ vs frontend/). If it's all one area, that's a single scope — don't manufacture splits.

Risk surfaces — flag the presence of any of these generic surfaces. For each one that fires, inject the matching focus-area line into reviewer prompts in Step 4:

Surface Inject this focus-area line
Authentication / authorization "Auth code touched — check for privilege escalation, missing access checks, and tokens/sessions handled correctly."
Database / schema migration "Schema migration touched — check locking, backfills, NOT NULL on existing rows, and that access rules/constraints are preserved."
Configuration / secrets "Config or secrets touched — confirm no secrets are hardcoded or logged, and environment-specific values aren't baked into source."
Dependency manifest "Dependency manifest changed — confirm new deps are pinned, sourced legitimately, and not duplicating existing functionality."
Critical-path / user-facing flow "Critical-path or user-facing flow touched — check error handling, input validation at boundaries, and that the happy path plus failure modes are covered."

Read the full file on GitHub · 280 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.

  1. 3d ago First seen · 280 lines · 143 tokens per session scan A c0a122dd0f1e

Subscribe to this mod's changes

review-work is a skill published in the GitHub repository peterkrueck/Claude-Code-Development-Kit (1,380 stars, last pushed 1mo ago), licensed MIT. It adds 143 tokens to every session and 2,961 once invoked, about $0.0007 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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