smithery/neversight

health-analyze

分析健康数据,计算健康评分并识别异常指标

Installation

$ npx skills add smithery/neversight --skill health-analyze

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,438 B
  • docs SUMMARY.md 82 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

health-analyze

分析健康指标数据,计算健康评分。

输入格式

输入 JSON 包含以下字段:

  • date: 日期字符串
  • data.temperature: 体温 (°C)
  • data.heart_rate: 心率 (bpm)
  • data.steps: 步数

评分规则

总分 100 分,分为三个维度:

  1. 体温 (30 分)

- 36.0 - 37.5°C: +30 分 - 其他: 0 分,标记为异常

  1. 心率 (30 分)

- 60 - 100 bpm: +30 分 - 其他: 0 分,标记为异常

  1. 步数 (40 分)

- ≥ 10000: +40 分 - ≥ 5000: +30 分 - < 5000: 0 分,标记为运动不足

输出格式

必须返回以下 JSON 结构:

{
  "status": "analyzed",
  "date": "<输入的日期>",
  "health_score": <0-100的数字>,
  "analysis": {
    "temperature_ok": <true/false>,
    "heart_rate_ok": <true/false>,
    "steps_ok": <true/false>,
    "issues": ["<问题描述1>", "<问题描述2>"]
  },
  "timestamp": "<ISO 8601 时间戳>"
}

示例

输入:

{"date": "2026-01-20", "data": {"temperature": 37.2, "heart_rate": 75, "steps": 8500}}

输出:

{
  "status": "analyzed",
  "date": "2026-01-20",
  "health_score": 90,
  "analysis": {
    "temperature_ok": true,
    "heart_rate_ok": true,
    "steps_ok": true,
    "issues": []
  },
  "timestamp": "2026-01-20T10:30:00Z"
}