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 agentmods add skills/marcusjellinghaus/mcp-workspace/implementation_finalisenpx skills add MarcusJellinghaus/mcp-workspace --skill implementation_finalisegit 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/implementation_finalise)<a href="https://agentmods.dev/skills/marcusjellinghaus/mcp-workspace/implementation_finalise"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-workspace/implementation_finalise.svg" alt="Measured on agentmods" 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 | $0.00004 | $0.00169 |
| Sonnet 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 5d 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:
- implementation_finalise — 100% identical, 0 lines differ
- implementation_finalise — 100% identical, 0 lines differ
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.
- 5d ago First seen · 53 lines · 8 tokens per session scan A 6e45e4086881
implementation_finalise is a skill published in the GitHub repository MarcusJellinghaus/mcp-workspace (50 stars, last pushed 3d ago), licensed MIT. It adds 8 tokens to every session and 338 once invoked, about $0.0000 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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