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CC Health

读取 HealthKit 里的运动、睡眠、心率、体重等健康数据, 在本地生成摘要。只读不写, 数据不离开本机。

The skillemall take

The skill reads HealthKit data—activity, sleep, heart rate, weight—and generates a local summary. Read-only, data stays on device.

Grade C with safety 100 points to code quality issues, not security gaps. Files contain 553 tokens of text but no scripts. Never ran on models, not tested in sandbox. No critical findings, yet quality_score at 57 suggests rough edges—likely incomplete data handling or fragile logic.

Install if you need quick HealthKit exports without overhead. Install with caution: test on your own data before production use.

kellyvv/PhoneClaw Agent Skills author: kellyvv 3 files body ≈ 553 tokens Open the sourcegithub.com↗ analyzed 4 d ago

读取 HealthKit 里的运动、睡眠、心率、体重等健康数据, 在本地生成摘要。只读不写, 数据不离开本机。

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

ProcedureData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
57
Run on models
none yet
Process rating
C
53/100
Has gaps
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: 3. 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")
  • note frontmatter-key unknown frontmatter key "name-zh"
  • note frontmatter-key unknown frontmatter key "icon"
  • note frontmatter-key unknown frontmatter key "disabled"
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "chip_prompt"
  • note frontmatter-key unknown frontmatter key "chip_label"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "examples"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 14 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 553 tokens
  • 100Running it twice. No mutating operations

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 55: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +1No license
  • +2Single-language instructions
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 14 items

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.