plan-review

plan-review is a skill for Claude Code, Codex from mvschwarz/openrig. It costs 35 tokens per session (769 once invoked), scanned A, original, Apache-2.0.

A review guide for checking a feature plan or requirements document from strategy, user experience, and engineering perspectives before development starts.

In plain words
What is it for?
Use it to assess product fit, user journeys, accessibility, interaction states, acceptance criteria, and technical feasibility.
Why use it?
It helps uncover unclear requirements, design gaps, scope problems, and implementation risks early.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/mvschwarz/openrig/plan-review
Any agent
npx skills add mvschwarz/openrig --skill plan-review
Clone the repo
git clone --depth 1 https://github.com/mvschwarz/openrig

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for plan-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/mvschwarz/openrig/plan-review.svg)](https://agentmods.dev/skills/mvschwarz/openrig/plan-review)
Your own site
<a href="https://agentmods.dev/skills/mvschwarz/openrig/plan-review"><img src="https://agentmods.dev/badge/skills/mvschwarz/openrig/plan-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 769 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00035 $0.00769
Opus 5 $0.00017 $0.00385
Sonnet 5 $0.00007 $0.00154
Haiku 4.5 $0.00003 $0.00077

Measured 6d ago against content hash bba9c1b1e537, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

plan-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/daemon/specs/agents/shared/skills/pm/plan-review/SKILL.md · 99 lines

How it starts

The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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)
  • requirements.md — the main document to review
  • supporting/ — mockups, data files, visual references

Step 2: Run All Three Reviews

Step 3: Synthesis

## Plan Review: [Feature Name]

**Date**: [date]
**Reviewed**: [requirements.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]

Read the full file on GitHub · 99 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 99 lines · 35 tokens per session scan A bba9c1b1e537

Subscribe to this mod's changes

plan-review is a skill published in the GitHub repository mvschwarz/openrig (65 stars, last pushed today), licensed Apache-2.0. It adds 35 tokens to every session and 769 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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