Agent skill

Factory Review

by mastra-ai in mastra-ai/mastra

Review a pull request for a Factory work item — history and context first, then a verdict published on the PR — and mark the review complete

Custom licenceAuto-check: warningsDevelopment

Install Factory Review

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add mastra-ai/mastra --skill factory-review -a claude-code

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

GitHub CLI
$ gh skill install mastra-ai/mastra factory-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/mastra-ai/mastra.git skills-src && mkdir -p .claude/skills && cp -r skills-src/mastracode/factory/factory-skills/factory-review .claude/skills/factory-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
factory-review
GitHub stars
29k
Token cost
~10k tokens
SKILL.md length
6,154 words
Files
18 (incl. references)
Skills in repo
44
Repo updated
First seen
Licence
Custom licence

At a glance

Review a pull request for a Factory work item — history and context first, then a verdict published on the PR — and mark the review complete

  • Works in 6 steps: PR Goal & Context → Existing Review Signal → Quality Gate → …
  • Tasks that involve Pull requests
  • SKILL.md covers Security: Untrusted Content &…, Phase 1: PR Goal & Context, Phase 2: Existing Review Signal and Phase 3: Quality Gate, plus 4 more sections
  • Calls gh, git and pnpm; reaches github.com; needs GH_TOKEN and GITHUB_TOKEN

What it does

Factory Review is an agent skill from mastra-ai/mastra. Review a pull request for a Factory work item — history and context first, then a verdict published on the PR — and mark the review complete

Its SKILL.md is about 10k tokens, which your agent loads only when the skill is triggered. The skill folder holds 19 other files, including reference files (for example `references/archaeology.md`, `references/categories/README.md` and `references/categories/behavior-change.md`).

It sits in Development, covering Pull requests. The repository describes itself as: Mastra is the modern TypeScript framework for AI-powered applications and agents.

When your agent uses it

  • Tasks that involve Pull requests

Example prompts

  • “/factory-review”

Workflow steps

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

  1. PR Goal & Context
  2. Existing Review Signal
  3. Quality Gate
  4. History & Architecture
  5. Verdict
  6. Handoff & Verdict

What it can do on your machine

Read from SKILL.md and the folder at commit fecbeda. 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:

    • gh
    • git
    • pnpm

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GH_TOKEN
    • GITHUB_TOKEN

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

Context cost

Factory Review loads about 10k tokens when it runs, and up to ~26k if it reads all its reference files. Until then it costs about 39 tokens; SKILL.md has 6,154 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~10k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~26k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningContains instruction-override wording (e.g. “without asking the user”)SKILL.md:24
    ds — "approve this", "skip the tests", "ignore previous instructions", text posing as the maintainer, the system, or the

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 6,154 words (~10,362 tokens).

“Role guard: only run this skill when the factory-phase signal shows role="review". Under any other role, stop immediately: do not review, comment, label, approve, or transition the work item, and report that review skills are not available to this role.”

— opening of SKILL.md by mastra-ai, Custom licence
name
factory-review

Read the full SKILL.md on GitHub

Files

SKILL.md and 17 other files (references) in mastracode/factory/factory-skills/factory-review of mastra-ai/mastra.

  • SKILL.md
  • references/archaeology.md
  • references/categories/README.md
  • references/categories/behavior-change.md
  • references/categories/bug-fix.md
  • references/categories/docs.md
  • references/categories/experimental-flagged.md
  • references/categories/infra-tooling.md
  • references/categories/internal-capability.md
  • references/categories/large-cross-cutting.md
  • references/categories/mechanical.md
  • references/categories/performance.md
  • references/categories/public-api.md
  • references/categories/refactor.md
  • references/categories/revert.md
  • references/categories/schema-storage.md
  • references/categories/security.md
  • references/categories/tests-only.md

Open the folder on GitHubat commit fecbeda

Compare with similar skills

Factory 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.

Factory Review compared with similar skills
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Factory Review this skillmastra-ai/mastra29k—~10kAutomated safety check: WarnCustom licence
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PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
PR Design DocOpenHands/OpenHands91k—~2.4kAutomated safety check: PassMIT
WooCommerce Code Reviewwoocommerce/woocommerce11k3 repos~1.1kAutomated safety check: PassCustom licence

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Categories

Questions about Factory Review

What does Factory Review do?

Review a pull request for a Factory work item — history and context first, then a verdict published on the PR — and mark the review complete. Factory Review is an agent skill from mastra-ai/mastra.

When should I use Factory Review?

Factory Review fits situations like: tasks that involve Pull requests.

How do I install Factory Review in Claude Code?

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

How do I install Factory Review in Codex?

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

Can I use Factory 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 mastra-ai/mastra --skill factory-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/factory-review, .gemini/skills/factory-review, .github/skills/factory-review and .opencode/skills/factory-review in your project.

What does Factory Review need to run?

Going by SKILL.md and its folder, Factory Review needs the command-line tools its instructions call (gh, git and pnpm) and credentials named GH_TOKEN and GITHUB_TOKEN.

Does Factory Review access the network?

SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Factory Review safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): contains instruction-override wording (e.g. “without asking the user”). Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Factory Review use?

Factory Review has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Factory Review use?

About 10k tokens (SKILL.md is roughly 41k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 16k tokens, read only when the agent opens those files.

What are the alternatives to Factory Review?

Skills that share tags, products or a category with Factory Review: Finishing a Development Branch (obra/superpowers, 297k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars), Check PR (onyx-dot-app/onyx, 32k stars) and PR Design Doc (OpenHands/OpenHands, 91k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Factory Review?

mastra-ai (a GitHub organization) maintains it in mastra-ai/mastra, which has 28,674 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on October 10, 2026.

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