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/jmrplens/gitlab-mcp-server/create-mcp-evaluationnpx skills add jmrplens/gitlab-mcp-server --skill create-mcp-evaluationgit clone --depth 1 https://github.com/jmrplens/gitlab-mcp-serverWrote 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/jmrplens/gitlab-mcp-server/create-mcp-evaluation)<a href="https://agentmods.dev/skills/jmrplens/gitlab-mcp-server/create-mcp-evaluation"><img src="https://agentmods.dev/badge/skills/jmrplens/gitlab-mcp-server/create-mcp-evaluation.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 | $0.00048 | $0.01175 |
| Opus 5 | $0.00024 | $0.00588 |
| Sonnet 5 | $0.00010 | $0.00235 |
| Haiku 4.5 | $0.00005 | $0.00118 |
Grade A, and why
create-mcp-evaluation 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.
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Server Evaluation Creator
Create comprehensive evaluations to test whether LLMs can effectively use your MCP server to answer realistic, complex questions using only the tools provided.
Overview
The quality of an MCP server is measured by how well its implementations (input/output schemas, descriptions, functionality) enable LLMs with no other context to answer realistic and difficult questions.
Process
Step 1: Tool Inspection
- List all tools available in the MCP server
- Understand input/output schemas, descriptions, and annotations
- Identify read-only vs. write operations
- Note pagination capabilities and limits
Step 2: Content Exploration
- Use READ-ONLY tools to explore available data
- Identify stable data points that won't change over time
- Map relationships between resources (projects → issues → comments → users)
- Note interesting patterns, edge cases, and complex relationships
Step 3: Question Design
Create 10 evaluation questions following these requirements:
Core Rules
- Questions MUST be independent (no dependency on other answers)
- Questions MUST require ONLY read-only, non-destructive operations
- Questions MUST be realistic — tasks humans with LLM assistance would care about
- Each answer MUST be a single, verifiable value (string comparison)
- Answers MUST be stable (won't change over time)
Complexity Guidelines
- Require multiple tool calls (potentially dozens)
- Multi-hop: answer depends on chaining information from multiple queries
- Require deep exploration, not surface-level keyword search
- Use synonyms and paraphrases, not direct keywords from target content
- May require extensive pagination through results
- Should stress-test tool return values across data modalities
Answer Diversity Cover diverse answer types:
- Names (user, project, group)
- IDs (project ID, issue IID)
- URLs and paths
- Timestamps and dates (specify format in question)
- Counts and quantities
- Boolean (True/False)
- Status values
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 · 133 lines · 48 tokens per session scan A 00fe99bf8e4c
create-mcp-evaluation is a skill published in the GitHub repository jmrplens/gitlab-mcp-server (33 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 1,175 once invoked, about $0.0002 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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