Borrowing it
Nothing to install: this file belongs to MarcusJellinghaus/mcp-workspace. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/MarcusJellinghaus/mcp-workspace/main/.claude/skills/plan_review/SKILL.mdgit clone --depth 1 https://github.com/MarcusJellinghaus/mcp-workspaceWrote 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/marcusjellinghaus/mcp-workspace/plan_review)<a href="https://agentmods.dev/skills/marcusjellinghaus/mcp-workspace/plan_review"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-workspace/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/marcusjellinghaus/mcp-workspace/plan_review"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-workspace/plan_review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00010 | $0.00344 |
| Opus 5 | $0.00005 | $0.00172 |
| Sonnet 5 | $0.00002 | $0.00069 |
| Haiku 4.5 | $0.00001 | $0.00034 |
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.
Copies of this mod
2 near-identical copies found in the catalogue:
- plan_review — 100% identical, 3 lines differ
- plan_review — 100% identical, 0 lines differ
What it actually says
Review Implementation Plan
First, ensure we're up to date:
Call mcp__mcp-workspace__git with command "fetch" and args ["origin"].
Use mcp__mcp-workspace__git with command "status" to check working directory state.
Confirm and display the current feature branch name.
Then review the plan:
Please review the project plan for a new feature in folder pr_info/steps.
Please revise the project plan with a balanced level of detail.
Please let me know if any complexity could be reduced.
Please let me know any questions / comments or suggestions you might have.
Please consider the already discussed and decided decisions (if any) under decisions. We do not need to challenge them again unless absolutely necessary.
Focus on:
- Completeness of implementation steps
- Appropriate level of detail
- Opportunities for simplification (KISS principle)
- Test coverage strategy
- Step granularity — each step should produce exactly one commit. Flag steps with multiple independent parts (A, B, C) that should be split.
- Potential risks or blockers
- Requirement changes — flag new dependencies (
pyproject.toml) that should be applied during planning, not deferred to implementation
For planning standards, see .claude/knowledge_base/planning_principles.md.
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 · 40 lines · 10 tokens per session scan A 99c8bebf2f9d
plan_review is a skill published in the GitHub repository MarcusJellinghaus/mcp-workspace (50 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 344 once invoked, about $0.0001 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.
Other skills, from other repositories
gitnexus-pr-review
Use when the user wants to review a pull request, understand what a PR changes, assess risk of merging, or check for missing test coverage. Examples: "Review this PR", "What does PR #42 change?", "Is this PR safe to merge?".
my-complex-skill
Production-ready Model Context Protocol (MCP) server for multi-agent AI consultations (Codex, Claude, Anti-Gravity, Mimo) with Minimax-M3 consensus synthesis.
gitnexus-debugging
Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug".
gitnexus-impact-analysis
Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?".
gitnexus-refactoring
Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: "Rename this function", "Extract this into a module", "Refactor this class", "Move this to a separate file".
gitnexus-cli
Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki".