Agent skill

Review

by HazAT in HazAT/pi-config

Coordinate a model-diverse local code review, automatically repair actionable findings with sequential workers, and re-review to a final verdict.

MITAuto-check passedDevelopment

Install Review

skills CLI
$ npx skills add HazAT/pi-config --skill review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HazAT/pi-config review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HazAT/pi-config.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/review .claude/skills/review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
review
GitHub stars
451
Token cost
~2.1k tokens
SKILL.md length
939 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Coordinate a model-diverse local code review, automatically repair actionable findings with sequential workers, and re-review to a final verdict.

  • Works in 4 steps: Establish context and scope → Run one review attempt → Repair NEEDS CHANGES automatically → …
  • Launched as an SC ensemble reviewer
  • SKILL.md covers Coordinator Mode, Delegated Reviewer Contract, Priorities and Review File Format
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Review is an agent skill from HazAT/pi-config. Coordinate a model-diverse local code review, automatically repair actionable findings with sequential workers, and re-review to a final verdict. Use for /review or when launched as an SC ensemble reviewer.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. The repository describes itself as: My personal pi coding agent configuration - skills and extensions. The licence is MIT.

When your agent uses it

  • Launched as an SC ensemble reviewer

Example prompts

  • “/review”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Establish context and scope
  2. Run one review attempt
  3. Repair NEEDS CHANGES automatically
  4. Finish visibly

What it can do on your machine

Read from SKILL.md and the folder at commit 655acd4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Review loads about 2.1k tokens when it runs. Until then it costs about 53 tokens; SKILL.md has 939 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~53
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HazAT/pi-config at commit 655acd4, republished under its MIT licence (© HazAT). 939 words, ~2,126 tokens.

Download SKILL.mdSave it as .claude/skills/review/SKILL.md (or your agent's skills folder).
name
review
description
Coordinate a model-diverse local code review, automatically repair actionable findings with sequential workers, and re-review to a final verdict. Use for /review or when launched as an SC ensemble reviewer.

Review and Repair

Review for correctness, security, regressions, and acceptance-criteria gaps. Delegated reviewers remain read-only. In coordinator mode, do not edit source directly; coordinate repair workers when the review requires changes.

Coordinator Mode

1. Establish context and scope

Derive the coordinator files before continuing:

bash
if [ -n "${PI_SESSION_FILE:-}" ]; then
  SESSION_FILE="$PI_SESSION_FILE"
elif [ -n "${CLAUDE_CODE_SESSION_ID:-}" ]; then
  SESSION_FILE="$HOME/.claude/projects/$(printf '%s' "${CLAUDE_PROJECT_DIR:-$PWD}" | tr '/.' '--')/${CLAUDE_CODE_SESSION_ID}.jsonl"
else
  echo "Error: /review requires a persistent session file (PI_SESSION_FILE or CLAUDE_CODE_SESSION_ID)." >&2
  exit 1
fi
test -f "$SESSION_FILE" || { echo "Error: session file not found: $SESSION_FILE" >&2; exit 1; }
PLAN_FILE="${SESSION_FILE%.jsonl}.plan.md"
TODOS_FILE="${SESSION_FILE%.jsonl}.todos.md"
REVIEW_FILE="${SESSION_FILE%.jsonl}.review.md"
  1. Require SESSION_FILE. Read PLAN_FILE or TODOS_FILE when each exists; they are optional.
  2. Recover intent from the current session and repository state when handovers are absent. Use the session-reader skill for focused extraction instead of parsing a large JSONL manually.
  3. Determine the exact base commit and current HEAD from managed-worktree and Git evidence. Ask only when a material scope ambiguity remains.
  4. Read ~/.pi/agent/skills/superconductor/SKILL.md and follow its live orchestration preflight.
2. Run one review attempt

Launch one model-diverse SC reviewer ensemble with three independent read-only Pi Chat UI sessions and unique attempt-scoped labels:

RolePi modelReasoningOwnsAvoids
leadopenai-codex/gpt-5.6-solhighbroad correctness, acceptance criteria, cross-report synthesisstyle-only polish
grokopenrouter/x-ai/grok-4.6configured defaultadversarial correctness, security, trust boundariesgeneral maintainability polish
kimiopenrouter/moonshotai/kimi-k3configured defaultregressions, cross-file behavior, frontend/accessibility, focused testsduplicating broad security review

At preflight, verify all three exact model IDs under the enabled pi provider with sc chat providers --json. Fail clearly rather than substituting a provider or model. Current sc team run cannot select a UI or model per role, so do not use it for this ensemble. Launch each role with sc layout run tabs, --provider pi, --ui chat, its exact --model, and --reasoning high only for the lead. The explicit Chat UI is required because SC's omitted/auto UI currently resolves delegated Pi launches to terminal mode rather than the configured Pi chat experience.

Give each role:

  • the exact diff/commit range and checkout;
  • a concise intent summary;
  • available plan/todos paths;
  • the session path only as optional fallback context;
  • its exclusive focus and the delegated contract below.

Start all three sessions without waiting between launches. Capture every returned stable target, wait for all three, and read each target's final report. Check target/provider errors and malformed or incomplete output; do not infer success from idle state.

After collecting the grok and kimi reports, send them to the same lead target for a synthesis turn. Require the lead to deduplicate claims, preserve disagreements, and return one proposed verdict with concrete findings. Wait for and read that same lead target again; do not launch a replacement lead.

Reviewers should not all run the same broad suite. Let the kimi role run focused tests when useful; the coordinator runs one definitive verification set after collecting reports.

Independently verify the lead's synthesis against the diff and specialist reports. A finding blocks approval only when it is concrete, introduced by the review range, and either P0/P1 or a P2 required by the selected acceptance criteria. P3 never blocks approval.

Write the current attempt to the supplied review file before any repair. Set APPROVED only when no blocking finding remains.

Show full SKILL.md (455 more words)Show less
3. Repair NEEDS CHANGES automatically

When blocking findings remain:

  1. Require a clean checkout and a committed review range before automatic repair. If the reviewed implementation includes uncommitted changes, write NEEDS CHANGES and stop rather than letting a worker absorb user-owned work into a commit.
  2. Group findings into at most three coherent, dependency-ordered repair tasks. Use IDs REVIEW-FIX-<round>-<n>.
  3. Launch one source-writing Pi worker at a time through raw SC. Give it the review path, available plan/todos paths, exact findings, acceptance criteria, and checkout. Require it to read ~/.pi/agent/skills/worker/SKILL.md.
  4. Require one focused verified commit per repair task and no push. The worker must leave task-owned files clean after its final verification.
  5. Wait and read the same stable worker target. Verify its reported SHA, diff scope, checks, and clean status independently before launching the next worker.
  6. Record repair task IDs, commit SHAs, and verification in the review file.
  7. Re-run a fresh independent review attempt against the original base through the new HEAD, using new ensemble labels.

Run at most two repair rounds. Stop early and report NEEDS CHANGES when a worker blocks, verification fails, a safety decision requires the user, or blocking findings remain after round two. Do not hide or downgrade unresolved findings to force approval.

4. Finish visibly

Always end with a normal assistant response containing:

  • final verdict;
  • review-file path;
  • reviewed range;
  • repair commit SHAs;
  • remaining blocking findings or none;
  • verification results.

Do not end after only writing or rereading the review file.

The coordinator owns every handover-file write. Do not create a captain protocol, custom state store, worktree, push, PR, merge, or cleanup action.

Delegated Reviewer Contract

When the launch prompt identifies this session as an ensemble reviewer:

  • Read the supplied handovers and optional session path directly; treat them as read-only.
  • Inspect the assigned diff and trace relevant unchanged logic before judging it.
  • Stay within the assigned focus and avoid duplicating another role's scope.
  • Run only safe, read-only, focused checks. Do not run a broad suite unless your assigned focus requires it.
  • Report only concrete, introduced, actionable issues. Include priority, file/line, impact, and suggested fix.
  • Do not edit files, write handovers, commit, push, or launch agents.
  • Finish with a concise normal assistant response containing APPROVED or NEEDS CHANGES, followed by findings and evidence. Do not call sc team report; these model-pinned Chat UI reviewers are collected from their stable targets.

Priorities

  • P0: production breakage, data loss, or exploitable security flaw.
  • P1: likely functional failure or serious foot gun.
  • P2: concrete scoped improvement; blocks only when required by acceptance criteria.
  • P3: minor polish; never blocks approval.

Review File Format

markdown
# Code Review

**Verdict:** APPROVED | NEEDS CHANGES
**Session:** `/absolute/path/to/session.jsonl`
**Plan:** `/absolute/path/to/session.plan.md` | not provided
**Todos:** `/absolute/path/to/session.todos.md` | not provided
**Reviewed commits:** [base..HEAD]
**Repair rounds:** 0 | 1 | 2

## Summary
[Concise evidence-based assessment]

## Verification
- `[command]` — [result]

## Findings
### [P1] [title]
- **File:** `path/to/file:line`
- **Issue:** [specific problem]
- **Impact:** [observable consequence]
- **Suggested fix:** [concrete direction]
- **State:** open | addressed by `<sha>`

## Repair Commits
- `REVIEW-FIX-1-1` — `<sha>` — [summary and verification]

## Independent Reports
- **lead (`openai-codex/gpt-5.6-sol`, high):** [synthesized verdict and evidence]
- **grok (`openrouter/x-ai/grok-4.6`):** [verdict and evidence]
- **kimi (`openrouter/moonshotai/kimi-k3`):** [verdict and evidence]

## Residual Risks
- None | [nonblocking risk]

Omit empty findings or repair sections. Preserve concise attempt and repair evidence when replacing the file with the final verdict.

© HazAT, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/review of HazAT/pi-config.

Open the folder on GitHubat commit 655acd4

Compare with similar skills

Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Review compared with similar skills
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Review this skillHazAT/pi-config451—~2.1kAutomated safety check: PassMIT
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Typescript Advanced Typesrolling-scopes/rsschool-app10k25 repos~4.2kAutomated safety check: PassMPL-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Code Review ChecklistshareAI-lab/learn-claude-code78k4 repos~1.1kAutomated safety check: PassMIT

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Categories

Questions about Review

What does Review do?

Coordinate a model-diverse local code review, automatically repair actionable findings with sequential workers, and re-review to a final verdict. Review is an agent skill from HazAT/pi-config. Coordinate a model-diverse local code review, automatically repair actionable findings with sequential workers, and re-review to a final verdict.

When should I use Review?

Review fits situations like: launched as an SC ensemble reviewer.

How do I install Review in Claude Code?

Run `npx skills add HazAT/pi-config --skill review -a claude-code`. Or copy the skill folder (skills/review in HazAT/pi-config) into .claude/skills/review in your project. Claude Code loads it when a task matches its description.

How do I install Review in Codex?

Run `npx skills add HazAT/pi-config --skill review -a codex`. Or copy the skill folder (skills/review in HazAT/pi-config) into .agents/skills/review in your project. Codex loads it when a task matches its description.

Can I use Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HazAT/pi-config --skill review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review, .gemini/skills/review, .github/skills/review and .opencode/skills/review in your project.

What does Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Review is instructions for the agent only.

Does Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Review use?

Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review use?

About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Review?

Skills that share tags, products or a category with Review: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review?

HazAT (a GitHub user) maintains it in HazAT/pi-config, which has 451 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on August 25, 2026.

Source: HazAT/pi-config on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.