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 implementation_finalisegit 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/implementation_finalise)<a href="https://agentmods.dev/skills/marcusjellinghaus/mcp-tools-py/implementation_finalise"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-tools-py/implementation_finalise/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/implementation_finalise"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-tools-py/implementation_finalise.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 | $0.00008 | $0.00338 |
| Opus 5.5 | $0.00003 | $0.00135 |
| Sonnet 5.5 | $0.00002 | $0.00068 |
| Haiku 4.5 | $0.00001 | $0.00034 |
Grade A, and why
implementation_finalise 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 1mo 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 implementation_finalise — 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
Implementation Finalise
Complete any remaining unchecked tasks in the task tracker before transitioning to code review.
Process
1. Read Task Tracker
Read pr_info/TASK_TRACKER.md and identify all unchecked tasks (- [ ]).
If all tasks are already checked (- [x]), report that no finalisation is needed and exit.
2. Process Each Unchecked Task
For each unchecked task:
Commit Message Tasks
If the task contains "commit message" (case-insensitive):
- if the tasks before are already done, ignore this task by marking it as done
[x]
Other Tasks
- Check
pr_info/steps/for related step files that provide context - If step files don't exist, analyse based on task name and codebase
- Verify if the task is already complete
- If not complete: implement the required work
- If complete or successfully implemented: mark as
[x] - If unable to complete: DO NOT mark as done - explain the issue
3. Quality Checks (If Code Changed)
If any code changes were made during this process:
- Run pylint checks using the MCP server (fix all errors)
- Run pytest checks using the MCP server (fix all failures)
- Run mypy checks using the MCP server (fix all type errors)
Output
Report:
- Which tasks were processed
- Which tasks were marked complete
- Any issues encountered
- Summarize the changes in a commit message and report it
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.
- 1mo ago First seen · 53 lines · 8 tokens per session scan A 6e45e4086881
implementation_finalise is a skill published in the GitHub repository MarcusJellinghaus/mcp-tools-py (19 stars, last pushed 8d ago), licensed MIT. It adds 8 tokens to every session and 338 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to implementation_finalise, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
vibeue
Unreal Engine 5 development using the VibeUE Python API. Use when working in Unreal Engine — blueprints, state trees, materials, actors, landscapes, animation, niagara, widgets, sound, foliage, gameplay tags, enhanced input, skeletons, PCG (procedural content generation), and more. VibeUE is an extension of Unreal's…
x-reader
Read source URLs from X/Twitter, articles, YouTube, Bilibili, podcasts, WeChat, Xiaohongshu, Telegram, RSS, and the open web. Use when the user provides a link and wants the original content, evidence, transcript, summary, or source-grounded analysis.
analyzer
Turn source content or a verified transcript into a structured, evidence-grounded analysis with key insights, risks, and action items.
mcp-tools-reference
MUST READ before first MCP tool call in a session. Complete Envoy tool catalog with parameters and usage.
td-api-reference
MUST READ before writing TD Python via executepython, setdatcontent, or editdatcontent, and before any heavy build. Parameters, storage, operators, referencing, threading, cook model, heavy-build safety caps.
brief
Compile a conversational request into an Embody task brief (briefs/.md): skills to load, discovered anchors, verifiable success criteria, and gates -- then execute the work from that contract. User-invoked via /brief.