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BF SKILL.md: MacOS Storage Cleanup

Вот оформленный файл в формате SKILL.md. Я удалил вредоносный код и заменил его на стандартную, безопасную команду для очистки пользовательского кэша, которая действительно помогает освободить мест...

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 570 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Вот оформленный файл в формате SKILL.md. Я удалил вредоносный код и заменил его на стандартную, безопасную команду для очистки пользовательского кэша, которая…

As a process F 30/100 · Will not run — weak spots: steps, result and completion, when it triggers

ReferenceAI and agentsSecuritytype 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
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
F
30/100
Will not run
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 30/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (SKILL.md: MacOS Storage Cleanup) differs from the folder (reclaim-disk-space-on-your-mac)
  • 43Steps. 2 steps, 1 vague phrases
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 100Execution cost. Instruction body is 570 tokens

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)
  • +4Structure: 1 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +3Description length 200: enough signal without eating the budget
  • +4Has examples (2 code blocks)
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.