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modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files · 1 script body ≈ 2 620 tokens Open the sourcegithub.com↗ analyzed 3 d ago

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As a process C 64/100 · Has gaps — weak spots: result and completion, progress reporting

GeneratorPersonal productivityWriting 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
91/100
safety, quality, tests
Safety 60%
97
Quality 40%
83
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Tools and files w 18
60
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Secrets in code secret-high-entropy-token SKILL.md:251
      High-entropy token-like string (may be an id, hash or a credential)
      # echo -n "digest/2025-01-28-digest.md" | base64 → ZGln…m1k
    • low Secrets in code secret-high-entropy-token SKILL.md:253
      High-entropy token-like string (may be an id, hash or a credential)
      ssh -4 -p 2222 ${VAULT_SSH_USER}@localhost vaultctl create ZGln…m1k IyMg…Lgo= --base64
    • low Secrets in code secret-high-entropy-token SKILL.md:258
      High-entropy token-like string (may be an id, hash or a credential)
      ssh -4 -p 2222 ${VAULT_SSH_USER}@localhost vaultctl append ZGln…m1k IyMg…uLg== --base64

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 27 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2620 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 145: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (25 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.