Borrowing it
Nothing to install: this file belongs to huifer/WellAlly-health. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/huifer/WellAlly-health/main/.claude/skills/fitness-analyzer/SKILL.mdgit clone --depth 1 https://github.com/huifer/WellAlly-healthWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/huifer/wellally-health/fitness-analyzer)<a href="https://agentmods.dev/skills/huifer/wellally-health/fitness-analyzer"><img src="https://agentmods.dev/badge/skills/huifer/wellally-health/fitness-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/huifer/wellally-health/fitness-analyzer"><img src="https://agentmods.dev/badge/skills/huifer/wellally-health/fitness-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.03258 |
| Opus 5 | $0.00018 | $0.01629 |
| Sonnet 5 | $0.00007 | $0.00652 |
| Haiku 4.5 | $0.00004 | $0.00326 |
Grade A, and why
fitness-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 432 lines — stays where its author put it; the contents beside it link to each section on GitHub.
运动分析器技能
分析运动数据，识别运动模式，评估健身进展，并提供个性化训练建议。
功能
1. 运动趋势分析
分析运动量、频率、强度的变化趋势，识别改善或需要调整的方面。
分析维度：
- 运动量趋势（时长、距离、卡路里）
- 运动频率趋势（每周运动天数）
- 强度分布变化（低/中/高强度占比）
- 运动类型偏好变化
输出：
- 趋势方向（改善/稳定/下降）
- 变化幅度和百分比
- 趋势显著性
- 改进建议
2. 运动进步追踪
追踪特定运动类型的进步情况，量化健身效果。
支持的进步追踪：
- 跑步进步：配速提升、距离增加、心率改善
- 力量训练进步：重量增加、容量提升、RPE变化
- 耐力进步：运动时长增加、距离延长
- 柔韧性进步：关节活动度改善
输出：
- 开始值 vs 当前值
- 改善百分比
- 进步可视化
- 达成的里程碑
3. 运动习惯分析
识别用户的运动习惯和模式。
分析内容：
- 常用运动时间（早晨/下午/晚上）
- 运动频率模式（每周几天）
- 运动类型偏好
- 休息日分布
- 运动一致性评分
输出：
- 习惯总结
- 一致性评分（0-100）
- 优化建议
- 习惯养成建议
4. 相关性分析
分析运动与其他健康指标的相关性。
支持的相关性分析：
- 运动 ↔ 体重：运动消耗与体重变化的关系
- 运动 ↔ 血压：运动对血压的长期影响
- 运动 ↔ 血糖：运动对血糖控制的效果
- 运动 ↔ 情绪/睡眠：运动对情绪和睡眠的影响
输出：
- 相关系数（-1到1）
- 相关性强度（弱/中/强）
- 统计显著性
- 因果关系推断
- 实践建议
5. 个性化建议生成
基于用户数据生成个性化运动建议。
建议类型：
- 运动频率建议：是否需要增加/减少运动频率
- 运动强度建议：强度调整建议
- 运动类型建议：推荐尝试的运动类型
- 运动时间建议：最佳运动时间
- 恢复建议：休息和恢复建议
建议依据：
- WHO/ACSM/AHA运动指南
- 用户运动历史数据
- 用户健康状况
- 用户健身目标
输出格式
趋势分析报告
# 运动趋势分析报告
## 分析周期
2025-03-20 至 2025-06-20（3个月）
## 运动量趋势
### 运动时长
- 趋势：⬆️ 上升
- 开始：平均120分钟/周
- 当前：平均180分钟/周
- 变化：+50%（+60分钟/周）
- 解读：运动量显著增加，表现优秀
### 卡路里消耗
- 趋势：⬆️ 上升
- 开始：平均960卡/周
- 当前：平均1440卡/周
- 变化：+50%
- 解读：运动消耗增加，有助于体重管理
### 运动距离
- 趋势：⬆️ 上升
- 开始：平均10公里/周
- 当前：平均20公里/周
- 变化：+100%
- 解读：耐力显著提升
## 运动频率
- 当前频率：4天/周
- 目标频率：4-5天/周
- 状态：✅ 达标
- 建议：保持当前频率
## 强度分布
| 强度 | 占比 | 变化 |
|------|------|------|
| 低强度 | 25% | +5% |
| 中等强度 | 55% | -10% |
| 高强度 | 20% | +5% |
**分析**：强度分布合理，中等强度占主导，符合有氧运动建议。
## 运动类型分布
| 运动类型 | 占比 |
|---------|------|
| 跑步 | 50% |
| 瑜伽 | 25% |
| 力量训练 | 25% |
**建议**：可以适当增加力量训练比例至30-40%。
## 洞察与建议
### 优势
1. ✅ 运动量稳定增长，(+50%)
2. ✅ 运动频率稳定，每周4天
3. ✅ 休息日充足，恢复良好
### 改进建议
1. 📈 每周增加2次力量训练
2. 📈 尝试不同运动类型避免单调
3. 📈 适当增加高强度间歇训练(HIIT)
### 警示
1. ⚠️ 注意运动强度不宜过高，控制在中等强度为主
相关性分析报告
# 运动与血压相关性分析
## 数据来源
- 运动数据：fitness-logs (2025-03-20 至 2025-06-20)
- 血压数据：hypertension-tracker (同期)
## 分析结果
### 相关系数
- 变量：每周运动时长 ↔ 收缩压
- 相关系数：r = -0.68
- 相关性强度：**强负相关**
- 统计显著性：p < 0.01 **高度显著**
### 解读
运动时长与收缩压呈强负相关，意味着：
- 运动越多，血压越低
- 每增加30分钟运动，收缩压平均下降3-5 mmHg
### 实践建议
1. ✅ 继续保持规律运动，每周5-7天
2. ✅ 每次运动30-60分钟，中等强度
3. ✅ 优先选择有氧运动（快走、慢跑、骑行）
4. ⚠️ 避免憋气动作和突然爆发性运动
### 医学参考
- AHA声明：规律有氧运动可降低收缩压5-7 mmHg
- 您的运动效果：降低约10 mmHg，效果显著！
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 432 lines · 37 tokens per session scan A df8f5738809d
fitness-analyzer is a skill published in the GitHub repository huifer/WellAlly-health (948 stars, last pushed 1mo ago), licensed MIT. It adds 37 tokens to every session and 3,258 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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