Agent skill

Review Team

by mvschwarz in mvschwarz/openrig

A skill your agent uses when assigned a review or when an authored review boundary is reached.

Apache-2.0Auto-check passedAgent Workflows

Install Review Team

skills CLI
$ npx skills add mvschwarz/openrig --skill review-team -a claude-code

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

GitHub CLI
$ gh skill install mvschwarz/openrig review-team --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/mvschwarz/openrig.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/_canonical/pods/review-team .claude/skills/review-team && 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-team
GitHub stars
6.6k
Token cost
~2.3k tokens
SKILL.md length
1,243 words
Files
1
Skills in repo
49
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when assigned a review or when an authored review boundary is reached.

  • Works in 5 steps: Context priming gate → Independent reviews → Cross-examination → …
  • Assigned a review
  • SKILL.md covers Entry and proportionality, Startup sequence, Context priming — always do… and Everyday review discipline, plus 5 more sections
  • Calls npm and npx

What it does

Review Team is an agent skill from mvschwarz/openrig. Use when assigned a review or when an authored review boundary is reached.

Its SKILL.md is about 2.3k 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 Agent Workflows. The repository describes itself as: Build your own network of agents from Claude Code, Codex and Pi: persistent teams with roles, shared context and owned work. The licence is Apache-2.0.

When your agent uses it

  • Assigned a review
  • An authored review boundary is reached

Example prompts

  • “/review-team”

Requirements

  • Node.js

Workflow steps

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

  1. Context priming gate
  2. Independent reviews
  3. Cross-examination
  4. Convergence and roundtable
  5. Final output

What it can do on your machine

Read from SKILL.md and the folder at commit 4b48ca2. 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

    Shell commands in SKILL.md call:

    • npm
    • npx

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

  • Network

    No URLs in SKILL.md. Its commands use npm and npx, which can reach the network depending on how they are called.

    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 Team loads about 2.3k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 1,243 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~22
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

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 mvschwarz/openrig at commit 4b48ca2, republished under its Apache-2.0 licence (© mvschwarz). 1,243 words, ~2,294 tokens.

Download SKILL.mdSave it as .claude/skills/review-team/SKILL.md (or your agent's skills folder).
name
review-team
description
Use when assigned a review or when an authored review boundary is reached.

Review Team

You are part of the review pod. Your value is fresh scrutiny that implementation and QA do not have.

Entry and proportionality

Run rig whoami --json, then resolve project.yaml -> mission.yaml -> active slice.yaml -> selected component or wave map -> addressed context. The complete lookup and precedence rule is docs/reference/product-journey-sdlc.md#resolve-the-selected-path (installed: $OPENRIG_HOME/reference/product-journey-sdlc.md#resolve-the-selected-path). Read the selected addresses and source needed for this task; skills available in your profile are capabilities, not a mandatory reading list. No composition means light Part A. Role names and idle seats add no gates. Explicit rigor and authored wave boundaries retain their named checks.

Start a review only for an explicit owner assignment or an authored component/wave review event. A visible milestone, idle queue, or available reviewer is not an assignment. At a wave boundary review the accumulated outcome once; preserve a named slice's explicit exception. Authors do not perform their own selected independent review.

Match the selected review to the consequence. A small diff gets a focused pass; the deep protocol below runs only when explicitly selected for named work. Importance, size or a prior finding alone cannot self-select it. If another review seems necessary, name the concrete unresolved risk to the owner while continuing the selected path.

Startup sequence

Derive the selection before forming a review position. If the assigned boundary has not arrived, record readiness and wait for its event; do not scan for work to turn into additional required reviews.

Context priming — always do this first

Before reviewing ANY code, you must understand the codebase context. Never review cold.

  1. Read the project's CLAUDE.md or equivalent conventions doc
  2. Read the as-built architecture docs for the subsystems you're reviewing
  3. Read the relevant planning/spec docs if they exist
  4. Understand the domain vocabulary and key invariants

If you have blanks — areas you don't understand — say so explicitly and fill them before forming opinions. A review built on misunderstood context is worse than no review.

For deep reviews, write a context proof before proceeding:

  • Subsystem purpose summary
  • Key invariants (must-not-break rules)
  • Architecture boundaries and constraints
  • PR/range intent and expected behavior
  • Unknowns / missing context
  • Confidence scores (0-100) per section

Everyday review discipline

These apply to every review, not just deep reviews.

Anti-slop lens

The primary question for every review: "Will an agent working on this code in 3 months find two ways to do the same thing?"

Check for:

  • Code duplication across files or subsystems
  • Pattern divergence from established codebase conventions
  • Naming inconsistencies that would confuse an agent scanning available commands
  • Parallel implementations where one should extend the other
  • Abstractions that don't earn their complexity
Empirical verification

Every claim you make must be verified against actual code. Not plausible inference. Not file-tree reasoning.

  • Run the tests yourself: npm test -w @openrig/daemon -- <relevant-suite>
  • Read the actual source at the line you're citing
  • If you claim something is broken, write a repro (even a quick npx tsx -e "...")
  • If you claim a test is missing, explain what input would break the code
  • If you claim duplication exists, cite both locations

A finding you haven't verified is a finding you shouldn't report.

Severity rating

Rate every finding clearly:

  • MUST-FIX — blocks merge. Broken behavior, security issue, or test suite failure.
  • HIGH — contract violation or honesty failure. Should fix before calling the range clean.
  • MEDIUM — real concern that affects maintenance or agent UX. Should fix soon.
  • LOW — polish, robustness, or minor inconsistency. Fix when convenient.
  • INFO — observation worth noting. Not a defect.
Reporting findings

Write review artifacts to disk so they survive compaction:

docs/review/<review-name>/01-review-<your-id>.md

Also report to the orchestrator or chatroom:

bash
rig send <orchestrator-session> "REVIEW: <title>
HIGH :: <file:line> :: <issue>
MEDIUM :: <file:line> :: <issue>
..." --verify

Or for rig-wide visibility:

bash
rig chatroom send <rig> "[review] <structured findings>"

When to review

Review the exact target when its selected entry condition holds. Read source and verification evidence for that target; a working tree may be the target when the assignment says so. Do not watch implementation increments or start a second review merely because a milestone appeared.

When there is no spec

When reviewing work that was implemented without a pre-existing spec (ad hoc, dogfood fixes, iterative patches):

  • Reconstruct what was intended from commit messages, chatroom history, and code context
  • Review against the reconstructed intent, not against a nonexistent plan
  • Ask: "Does this code deliver what it appears to intend? Are the contracts honest?"
  • This is called a hindsight review — you review forward from the code, not backward from a spec

Deep review protocol

Only when the owner or composition explicitly selects this protocol for named work, the orchestrator coordinates these phases. An ordinary review or two selected review legs do not implicitly select cross-examination, convergence, or roundtable.

Show full SKILL.md (490 more words)Show less
Phase 1: Context priming gate

Each reviewer independently reads context docs and writes a context proof (see above). The orchestrator reads both proofs and decides GO or NO-GO. No code review starts until the gate passes.

Phase 2: Independent reviews

Each reviewer reads the full diff/range independently and writes findings to disk:

docs/review/<review-name>/01-review-<your-id>.md

Do NOT read the other reviewer's work during this phase. Independence is the point — different reviewers catch different things.

Your independent review should cover:

  • Test posture (does the suite pass? are there regressions?)
  • Theme-by-theme or file-by-file analysis
  • Anti-slop audit
  • Answers to any review questions from the orchestrator or hindsight doc
  • Merge readiness verdict
Phase 3: Cross-examination

Each reviewer reads the other's independent review and responds to every finding:

  • AGREE — correct, evidence checks out
  • DISAGREE — incorrect, here is counter-evidence
  • PARTIALLY AGREE — valid concern but severity or details are wrong

You must also state:

  • What did they find that you missed? (Be honest about your blind spots)
  • What did you find that they missed?
  • Do their findings change any of your severity assessments?
  • Updated merge readiness verdict

Write cross-exam to disk:

docs/review/<review-name>/02-cross-review-<your-id>.md
Phase 4: Convergence and roundtable

The orchestration pod reads all reviews and cross-exams and writes a convergence synthesis classifying each finding as:

  • CONFIRMED — all reviewers agree
  • DISPUTED — disagreement exists with evidence on both sides
  • WITHDRAWN — originator retracted

Then a roundtable in the chatroom where all participants (reviewers + orchestrators) post positions, respond to each other, and converge on final findings and action items.

Culture for the roundtable:

  • Truth-seeking. Not contrarian for theater. Not agreeable to be nice.
  • Every participant posts an initial position
  • Every participant responds to at least one other's position
  • Every participant posts a final concur or amend
  • The host does not synthesize early — real back-and-forth first
Phase 5: Final output

The host writes the final roundtable document with:

  • Confirmed findings with severity
  • Final priority stack (P0 / P1 / P2)
  • Action items with owner
  • What the implementation team should NOT reopen

Reviewer behavioral awareness

If you are Claude (R1)
  • You tend to be strongest on architecture and weakest on edge-case honesty
  • You verify the happy path thoroughly but may miss failure-mode gaps
  • You should deliberately check: "What happens when this fails? What happens with bad input? What about the release-then-remove sequence?"
If you are Codex (R2)
  • You catch edge cases that Claude misses
  • You are thorough at empirical verification
  • You may over-weight severity on issues that are real but minor
  • You should deliberately check: "Is this actually a shipped defect or just a robustness wish?"
When reviewers disagree

Disagreement is useful. Keep your position grounded in evidence and let the orchestrator or roundtable resolve the conflict. Do not collapse your view just to create false consensus. If you're right, defend it. If you're wrong, retract it honestly.

When there is no assigned review

Make availability visible once, then wait for the selected boundary or assignment. An idle seat does not create a coverage audit, mandatory review, or new gate.

© mvschwarz, Apache-2.0. 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/_canonical/pods/review-team of mvschwarz/openrig.

Open the folder on GitHubat commit 4b48ca2

Compare with similar skills

Review Team 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 Team compared with similar skills
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Review Team this skillmvschwarz/openrig6.6k—~2.3kAutomated safety check: PassApache-2.0
MCP Server Builderanthropics/skills180k63 repos~2.3kAutomated safety check: PassApache-2.0
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k10 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Skill CreatorAzure/azqr79689 repos~8.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Review Team

What does Review Team do?

A skill your agent uses when assigned a review or when an authored review boundary is reached. Review Team is an agent skill from mvschwarz/openrig. Use when assigned a review or when an authored review boundary is reached.

When should I use Review Team?

Review Team fits situations like: assigned a review; an authored review boundary is reached.

How do I install Review Team in Claude Code?

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

How do I install Review Team in Codex?

Run `npx skills add mvschwarz/openrig --skill review-team -a codex`. Or copy the skill folder (skills/_canonical/pods/review-team in mvschwarz/openrig) into .agents/skills/review-team in your project. Codex loads it when a task matches its description.

Can I use Review Team 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 mvschwarz/openrig --skill review-team -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-team, .gemini/skills/review-team, .github/skills/review-team and .opencode/skills/review-team in your project.

What does Review Team need to run?

Going by SKILL.md and its folder, Review Team needs the command-line tools its instructions call (npm and npx). Our summary lists: Node.js.

Does Review Team access the network?

SKILL.md contains no URLs. Its commands use npm and npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Review Team 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 Team use?

Review Team is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Review Team use?

About 2.3k tokens (SKILL.md is roughly 9.2k 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 Team?

Skills that share tags, products or a category with Review Team: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Review Team?

mvschwarz (a GitHub user) maintains it in mvschwarz/openrig, which has 6,551 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 10, 2026.

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