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 issue_analysegit 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/issue_analyse)<a href="https://agentmods.dev/skills/marcusjellinghaus/mcp-tools-py/issue_analyse"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-tools-py/issue_analyse/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/issue_analyse"><img src="https://agentmods.dev/badge/skills/marcusjellinghaus/mcp-tools-py/issue_analyse.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 | $0.00011 | $0.00564 |
| Opus 5.5 | $0.00004 | $0.00226 |
| Sonnet 5.5 | $0.00002 | $0.00113 |
| Haiku 4.5 | $0.00001 | $0.00056 |
Grade A, and why
issue_analyse 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
88% identical to issue_analyse — 5 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.
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Analyse GitHub Issue
Fetch a GitHub issue and analyze its requirements, feasibility, and potential implementation approaches.
Resolve Issue Number
The user may provide an issue number as the argument (available as $ARGUMENTS).
If no issue number is provided:
- Read
.vscodeclaude_status.txtand extract the issue number from theIssue #NNNline - If the file doesn't exist or has no issue number, ask the user
Wait one second using mcp__mcp-tools-py__sleep with seconds: 1
Fetch the issue using mcp__mcp-workspace__github_issue_view.
Instructions
Analyze the issue:
Can we discuss this requirement / implementation idea and its feasibility? Please also look at the code base to understand the context (using the different tools with access to the project directory). Do not provide code yet!
At the end of our discussion, I want to have an even better issue description.
Decision-awareness:
If the issue contains a ## Decisions section, read it carefully:
- Do NOT re-ask topics that are already decided. Focus on aspects not yet covered.
- If any existing decision seems risky or questionable given what you see in the code, briefly note the concern — but don't block on it.
Constraints identification:
During the discussion, actively identify constraints and rationale — the "why" behind decisions, non-obvious gotchas, things that downstream steps (/create_plan, /implement) need to know. These will be captured in the issue via /issue_update.
Base Branch Handling:
If the issue contains a ### Base Branch section:
- Display the specified base branch prominently
- Verify the branch exists: call
mcp__mcp-workspace__gitwith command"ls_remote"and args["--heads", "origin", "<branch-name>"] - If the branch does NOT exist, show a clear warning: "⚠️ Warning: Base branch 'X' does not exist on remote. Branch creation will fail."
- Continue with the analysis (non-blocking error)
Focus on:
- Understanding the problem/feature request
- Technical feasibility
- Potential implementation approaches
- Questions that need clarification
- Impact on existing code
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 Changed · -2 lines 2ee6e6860585
- 1mo ago First seen · 62 lines · 11 tokens per session scan A b4708afa922a
issue_analyse is a skill published in the GitHub repository MarcusJellinghaus/mcp-tools-py (19 stars, last pushed 8d ago), licensed MIT. It adds 11 tokens to every session and 564 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to issue_analyse, differing in 5 lines, and is treated as a copy.
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