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.
npx skills add longranger2/claude-gpt-workflow --skill plan-reviewgit clone --depth 1 https://github.com/longranger2/claude-gpt-workflowWrote 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.
[](https://agentmods.dev/skills/longranger2/claude-gpt-workflow/plan-review)<a href="https://agentmods.dev/skills/longranger2/claude-gpt-workflow/plan-review"><img src="https://agentmods.dev/badge/skills/longranger2/claude-gpt-workflow/plan-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/longranger2/claude-gpt-workflow/plan-review"><img src="https://agentmods.dev/badge/skills/longranger2/claude-gpt-workflow/plan-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.01186 |
| Opus 5 | $0.00019 | $0.00593 |
| Sonnet 5 | $0.00008 | $0.00237 |
| Haiku 4.5 | $0.00004 | $0.00119 |
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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Review Skill
Purpose
When the user runs /plan-review {plan-file-path}, start the "adversarial plan iteration" workflow:
- I (Claude Code) ask Codex to perform a critical review of the specified plan.
- I read the review produced by Codex and evaluate whether its suggestions are sound.
- I revise the plan based on valid suggestions and write changes back to the original plan file.
- If the review status is
NEEDS_REVISION, I automatically ask Codex to review again. - Repeat until consensus is reached as
MOSTLY_GOODorAPPROVED.
Usage
/plan-review plans/my-feature-plan.md
Session Reuse
After each Codex invocation, extract session_id=xxx from the script output and save it as the session ID for the current task. In later Codex calls for the same task, pass --session <id> to reuse context so Codex remembers prior review history and can stay consistent across multiple rounds.
My Workflow (Claude Code)
Step 1: Determine the Review File
Derive the review file path from the plan file name:
plans/auth-refactor.md→reviews/auth-refactor-review.md- Rule:
reviews/{plan-file-name-without-.md}-review.md
If the review file already exists, this is not the first round, so Codex must track the resolution status of issues from the previous round.
Step 2: Ask Codex to Review the Plan
Use the /codex skill and give Codex the following instruction:
Read the contents of {plan-file-path} and review it critically as an independent third-party reviewer.
Requirements:
- Raise at least 10 concrete and actionable improvement points
- Each issue must include: issue description + exact location/reference in the plan + improvement suggestion
- Use severity levels: Critical > High > Medium > Low > Suggestion
- If {review-file-path} already exists, read it first and track the resolution status of previous issues in the new round
Analysis dimensions, choosing the relevant ones based on the plan type:
- Architectural soundness: overdesign vs underdesign, module boundaries, single responsibility
- Technology choices: rationale, alternatives, compatibility with the existing project stack
- Completeness: missing scenarios, overlooked edge cases, dependency and impact scope
- Feasibility: implementation complexity, performance risks, migration and compatibility concerns
- Engineering quality: whether it follows the Code Quality Hard Limits in `CLAUDE.md`
- User experience: interaction flow, error/loading states, i18n when relevant
- Security: authentication, authorization, data validation when relevant
Append the current review round to {review-file-path}, creating the file if it does not exist.
Separate rounds with `---` and append new rounds at the end of the file. Use this format:
---
## Round {N} — {YYYY-MM-DD}
### Overall Assessment
{2-3 sentence overall assessment}
**Rating**: {X}/10
### Previous Round Tracking (R2+ only)
| # | Issue | Status | Notes |
|---|-------|--------|-------|
### Issues
#### Issue 1 ({severity}): {title}
**Location**: {location in the plan}
{issue description}
**Suggestion**: {improvement suggestion}
... (at least 10 issues)
### Positive Aspects
- ...
### Summary
{Top 3 key issues}
**Consensus Status**: NEEDS_REVISION / MOSTLY_GOOD / APPROVED
Key principle: be a critical reviewer, not a yes-man. Every issue must be specific enough that someone knows how to revise the plan.
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.
- 10d ago First seen · 133 lines · 39 tokens per session scan A 6ee9435d586b
plan-review is a skill published in the GitHub repository longranger2/claude-gpt-workflow (78 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 1,186 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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