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/commands/report.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/commands/huifer/wellally-health/report)<a href="https://agentmods.dev/commands/huifer/wellally-health/report"><img src="https://agentmods.dev/badge/commands/huifer/wellally-health/report/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/commands/huifer/wellally-health/report"><img src="https://agentmods.dev/badge/commands/huifer/wellally-health/report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00017 | $0.04009 |
| Opus 5.5 | $0.00007 | $0.01604 |
| Sonnet 5.5 | $0.00003 | $0.00802 |
| Haiku 4.5 | $0.00002 | $0.00401 |
Grade A, and why
report 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 1mo 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 — 544 lines — stays where its author put it; the contents beside it link to each section on GitHub.
综合健康报告生成
生成专业的HTML格式健康报告，包含多种数据可视化图表，支持打印输出。
报告类型
1. 综合报告 - comprehensive
包含所有可用的健康数据章节，生成完整的健康报告。
默认包含的章节：
- 患者概况
- 生化检查分析
- 影像检查汇总
- 用药分析
- 辐射剂量追踪
- 过敏摘要
- 症状历史
- 手术记录
- 出院小结
2. 生化趋势分析 - biochemical
专注于生化检查数据的趋势分析和可视化。
3. 影像汇总 - imaging
影像检查记录的汇总和统计。
4. 用药分析 - medication
用药计划、依从性分析和用药历史。
5. 自定义报告 - custom
用户自定义包含的章节和数据范围。
时间范围参数
| 参数 | 说明 | 示例 |
|---|---|---|
all |
所有可用数据 | /report comprehensive all |
last_month |
上个月（自然月） | /report comprehensive last_month |
last_quarter |
上季度（3个月） | /report comprehensive last_quarter |
last_year |
去年（12个月） | /report comprehensive last_year |
YYYY-MM-DD,YYYY-MM-DD |
自定义起止日期 | /report custom 2024-01-01,2024-12-31 |
YYYY-MM-DD |
从某日期至今 | /report custom 2024-06-01 |
章节选择
使用 custom 报告类型时，可以通过逗号分隔指定包含的章节：
| 章节代码 | 说明 |
|---|---|
profile |
患者概况（年龄、BMI、体表面积等） |
biochemical |
生化检查趋势和统计 |
imaging |
影像检查汇总 |
medication |
用药分析和依从性 |
radiation |
辐射剂量追踪 |
allergies |
过敏摘要 |
symptoms |
症状历史和模式 |
surgeries |
手术记录 |
discharge |
出院小结 |
输出文件
默认输出到 reports/health-report-YYYY-MM-DD.html
可以通过 output 参数指定自定义文件名：
/report comprehensive all all my-health-report.html
执行步骤
步骤 1: 解析参数并确定时间范围
- 解析
action参数，确定报告类型 - 解析
date_range参数，计算起止日期 - 解析
sections参数，确定包含的章节 - 确定输出文件路径
步骤 2: 加载全局索引
读取 data/index.json，获取所有数据文件的索引信息。
如果索引文件不存在，扫描数据目录构建索引。
步骤 3: 收集数据
根据确定的章节，并行收集各类型数据：
3.1 收集患者概况
- 读取
data/profile.json - 提取：年龄、身高、体重、BMI、体表面积
3.2 收集生化检查数据
- 从索引中获取生化检查文件路径
- 读取指定时间范围内的所有生化检查记录
- 聚合指标数据，计算趋势
- 统计异常指标数量和分布
3.3 收集影像检查数据
- 从索引中获取影像检查文件路径
- 读取指定时间范围内的所有影像检查记录
- 统计检查类型、部位分布
- 提取关键发现
3.4 收集用药数据
- 读取
data/medications/medications.json（当前用药计划） - 读取
data/medication-logs/YYYY-MM/*.json（用药日志） - 计算用药依从性
- 统计漏服情况
3.5 收集辐射记录
- 读取
data/radiation-records.json - 计算累积剂量
- 按月份统计剂量分布
3.6 收集过敏数据
- 读取
data/allergies.json - 按严重程度分类
- 统计过敏类型分布
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.
- 1mo ago First seen · 544 lines · 17 tokens per session scan A 2d461854de40
report is a command published in the GitHub repository huifer/WellAlly-health (963 stars, last pushed 3mo ago), licensed MIT. It adds 17 tokens to every session and 4,009 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other commands, from other repositories
plot
Publication Polish. Runs after results-analysis (Phase 7). Audits all tables and figures produced in Phases 4–7, upgrades them to top-journal standards by calling the table and figure skills.
graphite-morphology-classify
Classify graphite in a cast-iron micrograph per ASTM A247 / ISO 945-1, quantify nodularity, and read the matrix — the single most diagnostic observation in a cast-iron case.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.