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个人全维度健康管理系统，中西医融合。当用户涉及运动训练计划、饮食营养建议、 健康数据记录追踪、中医体质辨识、节气养生、舌诊分析、性健康记录等话题时立即触发。 提供四位顾问（Coach Alex 运动教练 / Dr. Mei 营养师 / Analyst Ray 数据分析师 / Dr. Chen 中医体质顾问），支持深度建档和长期追踪。任何"帮我建档"、"记录今天运动"、 "我的体质"、"舌苔厚白"类请求均应触发本 skill。

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 41 files body ≈ 2 263 tokens Open the sourcegithub.com↗ analyzed 3 d ago

个人全维度健康管理系统，中西医融合。当用户涉及运动训练计划、饮食营养建议、 健康数据记录追踪、中医体质辨识、节气养生、舌诊分析、性健康记录等话题时立即触发。 提供四位顾问（Coach Alex 运动教练 / Dr.

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsSoftware developmentData and analyticstype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
D
43/100
Unfinished process
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
  • 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: 40. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "keywords"

Process rating: all ten parameters 43/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (healthfit) differs from the folder (healthfit-cn)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 67 steps
  • 100Execution cost. Instruction body is 2263 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 10 top-level sections: this looks like several domains in one skill
  • medium 25 test cases, all positive: not one "should refuse" or "should ask first"
  • low No test case covers injection arriving through data

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
  • -216 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 214: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 67 items
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (16 of 17)
  • +3All 4 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.