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/radiation-data.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/radiation-data)<a href="https://agentmods.dev/commands/huifer/wellally-health/radiation-data"><img src="https://agentmods.dev/badge/commands/huifer/wellally-health/radiation-data/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/radiation-data"><img src="https://agentmods.dev/badge/commands/huifer/wellally-health/radiation-data.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 | $0.00000 | $0.00752 |
| Opus 5 | $0.00000 | $0.00376 |
| Sonnet 5 | $0.00000 | $0.00150 |
| Haiku 4.5 | $0.00000 | $0.00075 |
Grade A, and why
radiation-data 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 10d 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.
What it actually says
辐射剂量计算参考数据
常见医学检查的辐射剂量参考值
CT检查 (单位: mSv)
- 头部CT: 2 mSv
- 胸部CT: 7 mSv
- 腹部CT: 8 mSv
- 盆腔CT: 6 mSv
- 脊柱CT: 6 mSv
- 四肢CT: 0.1 mSv
X光检查 (单位: mSv)
- 胸部X光: 0.1 mSv
- 腹部X光: 0.7 mSv
- 四肢X光: 0.01 mSv
- 牙齿X光: 0.005 mSv
其他检查
- PET-CT: 14 mSv
- 骨扫描: 6 mSv
- 血管造影: 5-15 mSv
- 乳腺钼靶: 0.4 mSv
辐射消散规律
医学影像检查产生的电离辐射主要通过以下方式代谢:
- 自然衰变: 碘、钡等造影剂通过自然衰变减少
- 人体代谢: 通过肾脏、肝脏等器官排出
- 物理半衰期: 不同放射性核素半衰期不同
简化计算模型(用于本系统)
半衰期模型:
- 大多数医学检查的辐射影响在 1年内 基本消散
- 采用 指数衰减模型: 当前剂量 = 初始剂量 × (0.5)^(天数/365)
- 年消散率: 约 50% 每年
辐射安全阈值
- 年平均自然本底辐射: 2.4 mSv/年
- 公众年剂量限值: 1 mSv (除自然本底外)
- 职业人员年剂量限值: 20 mSv/年
- 医学检查建议: 年累积剂量 < 10 mSv 为安全范围
体表面积计算
使用 Mosteller 公式:
体表面积 (m²) = √(身高(cm) × 体重(kg) / 3600)
剂量调整系数
根据体表面积调整辐射剂量:
- 标准体表面积: 1.73 m² (成年人)
- 调整系数: 实际体表面积 / 1.73
- 调整后剂量: 标准剂量 × 调整系数
辐射影响评估标准
低剂量 (< 1 mSv)
- 风险极低,无需特殊处理
中等剂量 (1-10 mSv)
- 需要记录
- 建议年度总结
高剂量 (10-50 mSv)
- 需要关注
- 建议间隔检查
- 记录累积剂量
极高剂量 (> 50 mSv)
- 需要医生评估
- 严格记录
- 考虑替代检查方案
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.
- 10d ago First seen · 79 lines · 0 tokens per session scan A 4eb7746ca485
radiation-data is a command published in the GitHub repository huifer/WellAlly-health (943 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 752 tokens. 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
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.