Agent skill

Doc Review Team

by michelangelo-ai in michelangelo-ai/michelangelo

Create a 3-agent team (engineer, tech-writer, product-manager) to review and improve docs for open-source quality.

Apache-2.0Auto-check passed

Install Doc Review Team

skills CLI
$ npx skills add michelangelo-ai/michelangelo --skill doc-review-team -a claude-code

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

GitHub CLI
$ gh skill install michelangelo-ai/michelangelo doc-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/michelangelo-ai/michelangelo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/docs/.claude/skills/doc-review-team .claude/skills/doc-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
doc-review-team
GitHub stars
118
Token cost
~329 tokens
SKILL.md length
131 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
Apache-2.0

At a glance

Create a 3-agent team (engineer, tech-writer, product-manager) to review and improve docs for open-source quality.

  • Works in 5 steps: All three start simultaneously → Engineer and PM send findings to… → Team lead forwards key findings to… → …
  • Reviewing any docs/ directory
  • SKILL.md covers Team Structure, Workflow and Broken Link Check
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Doc Review Team is an agent skill from michelangelo-ai/michelangelo. Create a 3-agent team (engineer, tech-writer, product-manager) to review and improve docs for open-source quality. Use when reviewing any docs/ directory or specific doc files.

Its SKILL.md is about 330 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Michelangelo AI: Uber's end-to-end machine learning platform. The licence is Apache-2.0.

When your agent uses it

  • Reviewing any docs/ directory
  • Specific doc files

Example prompts

  • “/doc-review-team”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. All three start simultaneously
  2. Engineer and PM send findings to tech-writer
  3. Team lead forwards key findings to tech-writer with actionable summaries
  4. Tech-writer writes improvements to disk
  5. Run broken link check after all files are written

What it can do on your machine

Read from SKILL.md and the folder at commit 491a9b2. 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.

    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

Doc Review Team loads about 329 tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 131 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~329

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 michelangelo-ai/michelangelo at commit 491a9b2, republished under its Apache-2.0 licence (© michelangelo-ai). 131 words, ~329 tokens.

Download SKILL.mdSave it as .claude/skills/doc-review-team/SKILL.md (or your agent's skills folder).
name
doc-review-team
description
Create a 3-agent team (engineer, tech-writer, product-manager) to review and improve docs for open-source quality. Use when reviewing any docs/ directory or specific doc files.
argument-hint
docs-path
user-invocable
true

Create a 3-agent team to review and improve documentation at $ARGUMENTS for open-source quality standards.

Team Structure

Spawn three teammates in parallel:

Engineer (agent: doc-engineer)

See doc-engineer agent definition.

Product Manager (agent: product-manager)

See product-manager agent definition.

Tech Writer (agent: tech-writer)

See tech-writer agent definition.

Workflow

  1. All three start simultaneously
  2. Engineer and PM send findings to tech-writer
  3. Team lead forwards key findings to tech-writer with actionable summaries
  4. Tech-writer writes improvements to disk
  5. Run broken link check after all files are written

After files are written, run an Explore agent to check all internal links:

  • Extract all relative links (./foo.md, ../bar/baz.md) from every .md file
  • Check each target file exists on disk
  • Ignore links inside code blocks
  • Report: file, line, broken link, suggested fix

© michelangelo-ai, 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 docs/.claude/skills/doc-review-team of michelangelo-ai/michelangelo.

Open the folder on GitHubat commit 491a9b2

Compare with similar skills

Doc 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.

Doc Review Team compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Doc Review Team this skillmichelangelo-ai/michelangelo118—~329Automated safety check: PassApache-2.0
Idea Refinementaddyosmani/agent-skills105k6 repos~2kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills105k6 repos~3.8kAutomated safety check: PassMIT
User Story Writerdeanpeters/Product-Manager-Skills7.2k2 repos~2.9kAutomated safety check: PassCustom licence
Game Changing FeaturesopenstatusHQ/data-table-filters2.3k3 repos~2.1kAutomated safety check: PassMIT
CCPM Project Managementautomazeio/ccpm8.4k—~1.1kAutomated safety check: PassMIT

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Questions about Doc Review Team

What does Doc Review Team do?

Create a 3-agent team (engineer, tech-writer, product-manager) to review and improve docs for open-source quality. Doc Review Team is an agent skill from michelangelo-ai/michelangelo. Create a 3-agent team (engineer, tech-writer, product-manager) to review and improve docs for open-source quality.

When should I use Doc Review Team?

Doc Review Team fits situations like: reviewing any docs/ directory; specific doc files.

How do I install Doc Review Team in Claude Code?

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

How do I install Doc Review Team in Codex?

Run `npx skills add michelangelo-ai/michelangelo --skill doc-review-team -a codex`. Or copy the skill folder (docs/.claude/skills/doc-review-team in michelangelo-ai/michelangelo) into .agents/skills/doc-review-team in your project. Codex loads it when a task matches its description.

Can I use Doc 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 michelangelo-ai/michelangelo --skill doc-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/doc-review-team, .gemini/skills/doc-review-team, .github/skills/doc-review-team and .opencode/skills/doc-review-team in your project.

What does Doc Review Team need to run?

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

Does Doc Review Team 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 Doc 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 Doc Review Team use?

Doc 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 Doc Review Team use?

About 329 tokens (SKILL.md is roughly 1.3k 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 Doc Review Team?

Skills that share tags, products or a category with Doc Review Team: Idea Refinement (addyosmani/agent-skills, 105k stars), Interview Me (addyosmani/agent-skills, 105k stars), User Story Writer (deanpeters/Product-Manager-Skills, 7.2k stars) and Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Doc Review Team?

michelangelo-ai (a GitHub organization) maintains it in michelangelo-ai/michelangelo, which has 118 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 10, 2026.

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