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 MarcusJellinghaus/mcp-tools-py --skill plan_approvegit clone --depth 1 https://github.com/MarcusJellinghaus/mcp-tools-pyWrote 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-tools-py/plan_approve)<a href="https://agentmods.dev/skills/marcusjellinghaus/mcp-tools-py/plan_approve"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-tools-py/plan_approve/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-tools-py/plan_approve"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-tools-py/plan_approve.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 | $0.00009 | $0.00156 |
| Opus 5 | $0.00005 | $0.00078 |
| Sonnet 5 | $0.00002 | $0.00031 |
| Haiku 4.5 | $0.00001 | $0.00016 |
Grade A, and why
plan_approve 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 9d 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.
This is a copy
100% identical to plan_approve — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Approve Implementation Plan
Approve the implementation plan and transition the issue to implementation-ready state.
Instructions:
- Run the set-status command to update the issue label:
mcp-coder gh-tool set-status status-05:plan-ready
- Confirm the status change was successful.
Note: If the command fails, report the error to the user. Do not use
--forceunless explicitly asked.
Effect: Changes issue status from status-04:plan-review to status-05:plan-ready.
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.
- 9d ago First seen · 22 lines · 9 tokens per session scan A d7e556f60327
plan_approve is a skill published in the GitHub repository MarcusJellinghaus/mcp-tools-py (18 stars, last pushed 2d ago), licensed MIT. It adds 9 tokens to every session and 156 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to plan_approve, differing in 0 lines, and is treated as a copy.
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