MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
A skill your agent uses when assigned a review or when an authored review boundary is reached.
$ npx skills add mvschwarz/openrig --skill review-team -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mvschwarz/openrig review-team --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "review-team" agent skill from https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-team into .claude/skills/review-team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-team", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-teamType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mvschwarz/openrig --skill review-team -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mvschwarz/openrig review-team --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mvschwarz/openrig.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/_canonical/pods/review-team .agents/skills/review-team && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "review-team" agent skill from https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-team into .agents/skills/review-team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-team", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mvschwarz/openrig --skill review-team -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mvschwarz/openrig review-team --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mvschwarz/openrig.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/_canonical/pods/review-team .cursor/skills/review-team && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "review-team" agent skill from https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-team into .cursor/skills/review-team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-team", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mvschwarz/openrig.git --path skills/_canonical/pods/review-team--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mvschwarz/openrig --skill review-team -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mvschwarz/openrig review-team --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mvschwarz/openrig.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/_canonical/pods/review-team .gemini/skills/review-team && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "review-team" agent skill from https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-team into .gemini/skills/review-team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-team", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mvschwarz/openrig review-teamInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mvschwarz/openrig --skill review-team -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mvschwarz/openrig.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/_canonical/pods/review-team .github/skills/review-team && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "review-team" agent skill from https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-team into .github/skills/review-team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-team", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mvschwarz/openrig --skill review-team -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mvschwarz/openrig review-team --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mvschwarz/openrig.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/_canonical/pods/review-team .opencode/skills/review-team && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "review-team" agent skill from https://github.com/mvschwarz/openrig/tree/main/skills/_canonical/pods/review-team into .opencode/skills/review-team/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-team", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
review-teamA 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.
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.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 4b48ca2. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
npmnpxFrom the folder's file list and the shell code blocks in SKILL.md.
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.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from mvschwarz/openrig at commit 4b48ca2, republished under its Apache-2.0 licence (© mvschwarz). 1,243 words, ~2,294 tokens.
.claude/skills/review-team/SKILL.md (or your agent's skills folder).You are part of the review pod. Your value is fresh scrutiny that implementation and QA do not have.
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.
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.
Before reviewing ANY code, you must understand the codebase context. Never review cold.
CLAUDE.md or equivalent conventions docIf 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:
These apply to every review, not just deep reviews.
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:
Every claim you make must be verified against actual code. Not plausible inference. Not file-tree reasoning.
npm test -w @openrig/daemon -- <relevant-suite>npx tsx -e "...")A finding you haven't verified is a finding you shouldn't report.
Rate every finding clearly:
Write review artifacts to disk so they survive compaction:
docs/review/<review-name>/01-review-<your-id>.mdAlso report to the orchestrator or chatroom:
rig send <orchestrator-session> "REVIEW: <title>
HIGH :: <file:line> :: <issue>
MEDIUM :: <file:line> :: <issue>
..." --verifyOr for rig-wide visibility:
rig chatroom send <rig> "[review] <structured findings>"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 reviewing work that was implemented without a pre-existing spec (ad hoc, dogfood fixes, iterative patches):
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.
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.
Each reviewer reads the full diff/range independently and writes findings to disk:
docs/review/<review-name>/01-review-<your-id>.mdDo NOT read the other reviewer's work during this phase. Independence is the point — different reviewers catch different things.
Your independent review should cover:
Each reviewer reads the other's independent review and responds to every finding:
You must also state:
Write cross-exam to disk:
docs/review/<review-name>/02-cross-review-<your-id>.mdThe orchestration pod reads all reviews and cross-exams and writes a convergence synthesis classifying each finding as:
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:
The host writes the final roundtable document with:
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.
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
Just SKILL.md in skills/_canonical/pods/review-team of mvschwarz/openrig.
Open the folder on GitHubat commit 4b48ca2
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Review Team this skillmvschwarz/openrig | 6.6k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Hook Development for Claude Code Pluginsanthropics/claude-plugins-official | 38k | 10 repos | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Using Superpowersfarm-fe/farm | 5.6k | 35 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Executing Plans Inlineobra/superpowers | 297k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Skill CreatorAzure/azqr | 796 | 89 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 |
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
anthropics/claude-plugins-official
Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.
farm-fe/farm
A skill your agent uses when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
obra/superpowers
Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.
Azure/azqr
Create new skills, modify and improve existing skills, and measure skill performance.
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
mvschwarz/openrig
Walks an agent through upgrading the OpenRig CLI and daemon one observed step at a time, keeping live seats alive and reconciling managed plugin files.
mvschwarz/openrig
Re-grounds a long-running agent in the current product outcome by running a path-based trace to the root of its topology and work trees.
mvschwarz/openrig
Helps set up a continuing agent software team for a real repository with OpenRig, choosing between manual work, queue handoffs and an explicit Workflow.
mvschwarz/openrig
Separates a stable agent seat's identity from its changing occupant, and records honest, two-part provenance whenever one occupant replaces another.
mvschwarz/openrig
Loads one section of a Markdown file by its path#h2-slug address with a bundled resolver script, for use outside OpenRig's context library.
mvschwarz/openrig
Covers authoring, inspecting, refreshing, promoting and deprecating named Agent Starters, the reusable starting points for agent seats in a rig.
Categories
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.
Review Team fits situations like: assigned a review; an authored review boundary is reached.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.