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Agent skill

Plan Review

by mvschwarz in mvschwarz/openrig

Multi-perspective review of a feature plan or requirements doc before development begins.

Apache-2.0Auto-check passedAgent Workflows

Install Plan Review

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

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

GitHub CLI
$ gh skill install mvschwarz/openrig plan-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/mvschwarz/openrig.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/_canonical/pm/plan-review .claude/skills/plan-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
plan-review
GitHub stars
5.9k
Token cost
~841 tokens
SKILL.md length
313 words
Files
1
Skills in repo
49
Repo updated
First seen
Licence
Apache-2.0

At a glance

Multi-perspective review of a feature plan or requirements doc before development begins.

  • Works in 7 steps: Strategy Review (CEO/Product Leader Lens) → Design Review (UX/Interaction Lens) → Engineering Feasibility (Technical Lens) → …
  • Agent Workflows work in your project
  • SKILL.md covers Three Review Lenses, Process and Guidelines
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Plan Review is an agent skill from mvschwarz/openrig. Multi-perspective review of a feature plan or requirements doc before development begins. Evaluates from strategy, design/UX, and engineering angles to catch gaps early.

Its SKILL.md is about 840 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

  • Agent Workflows work in your project

Example prompts

  • “/plan-review”

Workflow steps

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

  1. Strategy Review (CEO/Product Leader Lens)
  2. Design Review (UX/Interaction Lens)
  3. Engineering Feasibility (Technical Lens)
  4. Read the Material
  5. Run All Three Reviews
  6. Synthesis
  7. Generate Executive Summary

What it can do on your machine

Read from SKILL.md and the folder at commit 1f69831. 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 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

Plan Review loads about 841 tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 313 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~45
When it runs · the whole SKILL.md, loaded when a task matches
~841

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 1f69831, republished under its Apache-2.0 licence (© mvschwarz). 313 words, ~841 tokens.

Download SKILL.mdSave it as .claude/skills/plan-review/SKILL.md (or your agent's skills folder).
name
plan-review
description
Multi-perspective review of a feature plan or requirements doc before development begins. Evaluates from strategy, design/UX, and engineering angles to catch gaps early.

You are a multi-perspective plan reviewer. Before a feature moves from requirements to development, you evaluate it from three angles to catch gaps, scope drift, and missed opportunities.

Three Review Lenses

1. Strategy Review (CEO/Product Leader Lens)
  • Does this align with company growth objectives?
  • Which personas does this serve? Are they buyers, users, or influencers?
  • How does this compare to what competitors offer?
  • Is the scope right? Too ambitious or too focused?
  • What's the opportunity cost — what are we NOT building by doing this?
2. Design Review (UX/Interaction Lens)

Rate these dimensions (0-10):

  1. Information architecture — discoverable and logically organized?
  2. Interaction states — empty, loading, error, success, edge cases covered?
  3. User journey — matches how the persona actually works?
  4. Consistency — follows existing UI patterns?
  5. Accessibility — keyboard nav, screen readers, color contrast?
  6. AI integration — if AI-powered, is it natural and trustworthy?
3. Engineering Feasibility (Technical Lens)
  • Are acceptance criteria specific enough that a dev won't need to guess?
  • Are there data model implications needing early discussion?
  • Are there dependencies on other features or systems?
  • Are there performance/scale considerations?
  • Is the scope realistic for the implied timeline?

Process

Step 1: Read the Material

Read all available docs in the feature folder:

  • validation.md — office hours verdict, demand evidence, wedge scope (if exists)
  • background.md — customer drivers, competitive context (if exists)
  • SPEC.md — the main document to review
  • supporting/ — mockups, data files, visual references
Step 2: Run All Three Reviews
Step 3: Synthesis
markdown
## Plan Review: [Feature Name]

**Date**: [date]
**Reviewed**: [SPEC.md path]

### Strategy Assessment
**Score: [1-10]**
- [Key findings]

### Design Assessment
**Score: [1-10]**
| Dimension | Score | Notes |
|-----------|-------|-------|
| Information Architecture | X/10 | [notes] |
| Interaction States | X/10 | [notes] |
| User Journey | X/10 | [notes] |
| Consistency | X/10 | [notes] |
| Accessibility | X/10 | [notes] |
| AI Integration | X/10 | [notes] |

### Engineering Feasibility
**Score: [1-10]**
- [Key findings]

### Issues Found

#### Blocking (must fix before dev)
1. [Issue with specific reference to requirement]

#### Important (should fix, but not blocking)
1. [Issue]

#### Suggestions (nice to have)
1. [Suggestion]

### Recommended Actions
- [Specific actions before proceeding to development]
Step 4: Generate Executive Summary

After the review is complete and issues are resolved, generate an executive summary using the exec-summary skill. Save it to the feature folder as executive-summary.md.

Guidelines

  • Be specific. Cite exact requirements that have issues.
  • Reference real context. Check personas, competitors, and existing features.
  • Don't do the dev's job. The engineering lens is about PM-side clarity, not architecture.
  • Praise what's good. Helps the PM know what to keep doing.

© 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/pm/plan-review of mvschwarz/openrig.

Open the folder on GitHubat commit 1f69831

Compare with similar skills

Plan 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.

Plan Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Plan Review this skillmvschwarz/openrig5.9k—~841Automated safety check: PassApache-2.0
MCP Server Builderanthropics/skills180k64 repos~2.3kAutomated safety check: PassApache-2.0
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k11 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers296k2 repos~5.1kAutomated safety check: PassMIT
Claude Code Agent Developmentanthropics/claude-plugins-official38k8 repos~2.8kAutomated safety check: PassApache-2.0

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Categories

Questions about Plan Review

What does Plan Review do?

Multi-perspective review of a feature plan or requirements doc before development begins. Plan Review is an agent skill from mvschwarz/openrig. Multi-perspective review of a feature plan or requirements doc before development begins.

When should I use Plan Review?

Plan Review fits situations like: agent Workflows work in your project.

How do I install Plan Review in Claude Code?

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

How do I install Plan Review in Codex?

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

Can I use Plan 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 mvschwarz/openrig --skill plan-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/plan-review, .gemini/skills/plan-review, .github/skills/plan-review and .opencode/skills/plan-review in your project.

What does Plan Review need to run?

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

Does Plan 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 Plan 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 Plan Review use?

Plan Review 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 Plan Review use?

About 841 tokens (SKILL.md is roughly 3.4k 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 Plan Review?

Skills that share tags, products or a category with Plan Review: 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, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Plan Review?

mvschwarz (a GitHub user) maintains it in mvschwarz/openrig, which has 5,854 GitHub stars. The repository holds 49 skills in this directory. The repository was last updated on October 8, 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.