create-mcp-evaluation

create-mcp-evaluation is a skill for Claude Code, Codex from jmrplens/gitlab-mcp-server. It costs 48 tokens per session (1,175 once invoked), scanned A, original, MIT.

A method for creating question-and-answer tests for an MCP server. MCP is a way for AI assistants to use tools and access connected data.

In plain words
What is it for?
It helps inspect tools, explore readable data, and create independent evaluation questions that measure server quality without changing data.
Why use it?
It checks whether an AI can complete realistic tasks using only the server’s available tools and descriptions.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/jmrplens/gitlab-mcp-server/create-mcp-evaluation
Any agent
npx skills add jmrplens/gitlab-mcp-server --skill create-mcp-evaluation
Clone the repo
git clone --depth 1 https://github.com/jmrplens/gitlab-mcp-server

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for create-mcp-evaluation

README.md
[![agentmods](https://agentmods.dev/badge/skills/jmrplens/gitlab-mcp-server/create-mcp-evaluation.svg)](https://agentmods.dev/skills/jmrplens/gitlab-mcp-server/create-mcp-evaluation)
Your own site
<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>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,175 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 5d ago against content hash 00fe99bf8e4c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

.github/skills/create-mcp-evaluation/SKILL.md · 133 lines

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

  1. List all tools available in the MCP server
  2. Understand input/output schemas, descriptions, and annotations
  3. Identify read-only vs. write operations
  4. Note pagination capabilities and limits

Step 2: Content Exploration

  1. Use READ-ONLY tools to explore available data
  2. Identify stable data points that won't change over time
  3. Map relationships between resources (projects → issues → comments → users)
  4. 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

Read the full file on GitHub · 133 lines

Changes

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.

  1. 5d ago First seen · 133 lines · 48 tokens per session scan A 00fe99bf8e4c

Subscribe to this mod's changes

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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