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AC mcp-integration

Use Model Context Protocol servers to access external tools and data sources. Enable AI agents to discover and execute tools from configured MCP servers (legal databases, APIs, database connectors, weather services, etc.).

modbender/skill-library-mcp Agent Skills author: modbender MIT 18 files body ≈ 1 790 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Use Model Context Protocol servers to access external tools and data sources.

As a process C 53/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency

IntegrationAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
95
Quality 40%
92
Run on models
none yet
Process rating
C
53/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 5

    ✓ No critical or high findings

    Medium and low: 5
    • low Secrets in code secret-high-entropy-token package-lock.json:85
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…GLi+2W/6ao+6Y7gu/RCwR…Kng==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:264
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…GLw+xYSd…cqA==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:319
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…FrF+LTRo…W3g==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:328
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…A6j+hAmM…GbS+kf5c…csw==",
      detector
    • low Secrets in code secret-high-entropy-token package-lock.json:337
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…5bm+c2gQ…aG5+esrLODihIorn+Pe6F…dXA==",
      detector

    Files scanned: 16. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 53/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (mcp-integration) differs from the folder (mcp-adapter)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 50 steps, 1 vague phrases
    • 100Execution cost. Instruction body is 1790 tokens
    • 100Running it twice. No mutating operations
    • low 11 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +3Description length 222: enough signal without eating the budget
    • +4Structure: 29 headings
    • +3Step-by-step instructions: 50 items
    • +3Output format is stated explicitly
    • +4Has examples (13 code blocks)
    • +4Reference files are cited in the instructions (5 of 9)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.