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BF tool-design

Build tools that agents can use effectively, including architectural reduction patterns

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 3 860 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Build tools that agents can use effectively, including architectural reduction patterns

As a process F 46/100 · Will not run — References files that are not bundled: references/architectural_reduction.md, references/best_practices.md

GeneratorAI and agentstype 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
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
F
46/100
Will not run
References files that are not bundled: references/architectural_reduction.md, references/best_practices.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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 · 0

✓ No critical or high findings

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: references/architectural_reduction.md
  • warning missing-ref reference to a missing file: references/best_practices.md
  • note frontmatter-key unknown frontmatter key "source"
  • note frontmatter-key unknown frontmatter key "risk"

Process rating: all ten parameters 46/100

Will not run. References files that are not bundled: references/architectural_reduction.md, references/best_practices.md
  • 0Tools and files. 2 referenced file(s) missing: references/architectural_reduction.md, references/best_practices.md
  • 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
  • 30Running it twice. 8 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 55 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3860 tokens
  • low 10 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)
  • +3Description length 87: 120–800 characters recommended
  • +1No license
  • +2Single-language instructions
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 55 items
  • +3Output format is stated explicitly
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.