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/specialist.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/specialist)<a href="https://agentmods.dev/commands/huifer/wellally-health/specialist"><img src="https://agentmods.dev/badge/commands/huifer/wellally-health/specialist/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/specialist"><img src="https://agentmods.dev/badge/commands/huifer/wellally-health/specialist.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 | $0.00011 | $0.02051 |
| Opus 5 | $0.00005 | $0.01026 |
| Sonnet 5 | $0.00002 | $0.00410 |
| Haiku 4.5 | $0.00001 | $0.00205 |
Grade A, and why
specialist 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 11d 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 — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
您需要根据用户指定的专科,启动对应的专科专家进行深入分析。
支持的专科列表
内科系统
| 专科代码 | 专科名称 | Skill 文件 | 擅长领域 |
|---|---|---|---|
| cardio | 心内科 | cardiology.md | 心脏病、高血压、血脂异常 |
| endo | 内分泌科 | endocrinology.md | 糖尿病、甲状腺疾病 |
| gastro | 消化科 | gastroenterology.md | 肝病、胃肠疾病 |
| nephro | 肾内科 | nephrology.md | 肾脏病、电解质紊乱 |
| heme | 血液科 | hematology.md | 贫血、凝血异常 |
| resp | 呼吸科 | respiratory.md | 肺部感染、肺结节 |
| neuro | 神经内科 | neurology.md | 脑血管病、头痛头晕 |
| onco | 肿瘤科 | oncology.md | 肿瘤标志物、肿瘤筛查 |
外科及专科系统
| 专科代码 | 专科名称 | Skill 文件 | 擅长领域 |
|---|---|---|---|
| ortho | 骨科 | orthopedics.md | 骨折、关节炎、骨质疏松 |
| derma | 皮肤科 | dermatology.md | 湿疹、痤疮、皮肤肿瘤 |
| pedia | 儿科 | pediatrics.md | 儿童发育、新生儿疾病 |
| gyne | 妇科 | gynecology.md | 月经疾病、妇科肿瘤 |
综合系统
| 专科代码 | 专科名称 | Skill 文件 | 擅长领域 |
|---|---|---|---|
| general | 全科 | general.md | 综合评估、慢病管理 |
| psych | 精神科 | psychiatry.md | 情绪障碍、心理健康 |
使用方法
# 查询所有支持的专科
/specialist list
# 咨询特定专科
/specialist <专科代码> [参数]
# 示例:
/specialist cardio recent 3
/specialist endo all
/specialist ortho all
/specialist derma date 2025-12-31
/specialist pedia recent 5
/specialist gyne all
执行流程
1. 验证专科代码
检查用户指定的专科代码是否有效。如果无效,列出所有可用的专科。
2. 读取专科 Skill 定义
根据专科代码,读取对应的 skill 定义文件:
.claude/specialists/<专科对应的md文件>
3. 收集医疗数据
根据用户参数读取相关医疗数据:
all: 所有数据recent N: 最近N条记录date YYYY-MM-DD: 指定日期- 无参数: 最近3条记录
新增:慢性病数据读取 对于特定专科,还需读取相关的慢性病管理数据:
- cardio(心内科):读取
data/hypertension-tracker.json(高血压管理数据) - endo(内分泌科):读取
data/diabetes-tracker.json(糖尿病管理数据) - resp(呼吸科):读取
data/copd-tracker.json(COPD管理数据) - nephro(肾内科):读取高血压和糖尿病管理数据(评估肾脏风险)
数据读取优先级:
- 慢性病管理数据(如存在)
- 检查报告数据(/save-report 保存的)
- 其他相关医疗记录
4. 启动专科分析
使用 Task 工具启动该专科的 subagent,将:
- 专科 skill 定义内容
- 医疗数据内容
- 分析要求
传递给 subagent。
5. 展示分析报告
将 subagent 返回的专科分析报告直接展示给用户。
示例 Prompt(用于启动 subagent)
您是{{专科名称}}专家。请按照以下 Skill 定义进行医疗数据分析:
## Skill 定义
{{读取 .claude/specialists/{{对应的md文件}} 的完整内容}}
## 患者医疗数据
### 慢性病管理情况(如有)
{{读取对应的慢性病数据文件:
- cardio: data/hypertension-tracker.json
- endo: data/diabetes-tracker.json
- resp: data/copd-tracker.json
- nephro: data/hypertension-tracker.json + data/diabetes-tracker.json
}}
### 近期检查数据
{{读取相关的检查报告数据}}
## 分析要求
1. 严格按照 Skill 定义的格式输出分析报告
2. **优先分析慢性病管理情况**(如存在):
- 诊断时间和分类
- 控制情况(达标率、平均值等)
- 靶器官损害/并发症状态
- 风险评估
3. 结合检查报告数据综合分析
4. 严格遵守以下安全红线:
- 不给出具体用药剂量
- 不直接开具处方药名
- 不判断生死预后
- 不替代医生诊断
5. 提供具体可行的建议
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.
- 11d ago First seen · 249 lines · 11 tokens per session scan A 61ecf1463a2f
specialist is a command published in the GitHub repository huifer/WellAlly-health (947 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 2,051 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
health
Run health checks on the Claude orchestration system.
health
Scan all projects for stale research, forgotten ADRs, unresolved review conditions, orphaned artifacts, missing traceability, and version drift.
roster-doctor
Health check and dev-environment pre-flight for the roster install and its build/test/lint tooling.
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.