Xpersona
agentCLAWHUBUnverified

unisound-health-risk-assessment

体检健康风险评估。基于体检报告对心脑血管、糖代谢、肿瘤、代谢综合征等多维度健康风险进行分级，生成含时间节点的个性化健康管理方案（JSON + 健康风险报告）。 Skill: unisound-health-risk-assessment Owner: unisound-llm Summary: 体检健康风险评估。基于体检报告对心脑血管、糖代谢、肿瘤、代谢综合征等多维度健康风险进行分级，生成含时间节点的个性化健康管理方案（JSON + 健康风险报告）。 Tags: latest:1.0.2 Version history: v1.0.2 | 2026-07-16T07:51:50.763Z | user - Removed the unnecessary skill-card.md file to keep only essential files in the skill package. - Updated default model parameter from "u1-insuremed" to "u2-med" for the medical large model. v1.0

OpenClaw
View on ClawHubHomepage

Rank

62

Safety

84

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.0.2

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

  • Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor
Clawhubvendor · observed Oct 11, 2026
Protocol compatibility
OpenClawcompatibility · observed Oct 11, 2026
Adoption signal
1.1K downloadsadoption · observed Oct 11, 2026
Latest release
1.0.2release · observed Jul 16, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s1770nyybxj4gn0vk38n6wr6k584x8ea:unisound-health-risk-assessment
  1. Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
  2. Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-unisound-llm-unisound-health-risk-assessment/snapshot"

Documentation

CLAWHUB

13,180 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: health-exam-health-risk-assessment
description: 体检健康风险评估。基于体检报告对心脑血管、糖代谢、肿瘤、代谢综合征等多维度健康风险进行分级，生成含时间节点的个性化健康管理方案（JSON + 健康风险报告）。
metadata:
  {
    "openclaw":
      {
        "emoji": "⚠️"
      }
  }
---

# 健康风险评估

概述
----
面向**体检中心/健康管理机构**，给定受检者体检报告，本技能会：

- 对7大健康风险维度进行分级评估：
  - 心脑血管风险
  - 糖代谢风险
  - 代谢综合征
  - 肿瘤风险（基于标志物和影像发现）
  - 肝脏健康
  - 肾脏健康
  - 甲状腺健康
- 给出整体风险级别（低/中/高/极高）
- 生成含立即行动、3个月目标、1年目标的健康管理计划
- 提供个性化的饮食、运动、睡眠建议
- 给出专科转诊建议

与"体检报告整体解读"的区别：本技能重点在**风险前瞻性评估**和**管理计划制定**，适合作为检后健康管理服务的入口。

数据安全、隐私与伦理声明
------------------------
- **最小必要原则**：仅处理风险评估所必需的检查数据；不要求包含直接身份标识。
- **严格脱敏**：发送前对可识别身份信息进行脱敏处理。
- **不做本地持久化**：仅在内存中短暂处理；**本次调用结束即销毁**。
- **医疗边界**：本技能输出为风险评估参考，不替代专科诊断；高风险人群请务必就医。

输入格式
--------
纯文本（UTF-8），建议提供完整体检报告，信息越全评估越精准，例如：

```text
受检者：男，50岁，公司管理层，吸烟史20年（每天约1包），偶尔饮酒
BMI：27.8，腰围93cm
血压：148/94mmHg
血糖：空腹6.8mmol/L，HbA1c 6.4%
血脂：TC 6.2mmol/L，LDL 4.0mmol/L，HDL 0.9mmol/L，TG 3.1mmol/L
肝功：ALT 68U/L，AST 52U/L，GGT 78U/L
肾功：肌酐88μmol/L，尿酸480μmol/L
肿瘤标志物：CEA 5.8ng/mL（↑，参考<5），AFP正常，PSA正常
心电图：窦性心律，左室高电压
超声：中度脂肪肝，甲状腺右叶3mm低回声结节（TI-RADS 3类）
```

也支持 JSON 格式（包含 `text`/`content`/`report` 字段的对象）。

快速开始
--------

```bash
# 从 skills 目录运行
python3 health-exam/report-interpret/health-risk-assessment/scripts/run.py \
  --input data/health-exam-risk/case-001.txt \
  --appkey <your-appkey>

# 保存输出到文件
python3 health-exam/report-interpret/health-risk-assessment/scripts/run.py \
  --input data/health-exam-risk/case-001.txt \
  --appkey <your-appkey> \
  --output runs/health-exam-risk/case-001.json
```

参数说明
--------
- `--input PATH`：**必填**。体检报告文件路径（txt 或 json，UTF-8）。
- `--appkey STRING`：**必填**。调用内部医疗大模型的鉴权 key，由平台分配。
- `--output PATH`：输出文件路径（默认：打印到 stdout）。
- `--base URL`：内部大模型 base URL（默认：`https://maas-api.hivoice.cn/v1`）。
- `--model STRING`：模型名称（默认：`u2-med`）。
- `--timeout SECONDS`：HTTP 超时秒数；`0` 表示一直等待（默认：0）。
- `--encoding STRING`：输入文件编码（默认：`utf-8`）。

输出约定
--------
输出分两部分：

**JSON 结构**：

```json
{
  "risk_profile": {
    "age": "50岁",
    "gender": "男",
    "overall_risk_level": "高风险"
  },
  "risk_dimensions": [
    {
      "dimension": "心脑血管风险",
      "risk_level": "高",
      "risk_factors": ["高血压（148/94mmHg）", "高LDL（4.0mmol/L）", "低HDL（0.9mmol/L）", "吸烟20年", "超重"],
      "protective_factors": [],
      "10_year_risk_estimate": "较高（Framingham评分估算>20%）",
      "priority_interventions": ["戒烟", "就医评估降脂降压治疗", "增加有氧运动"]
    }
  ],
  "health_management_plan": {
    "immediate_actions": [
      {"action": "前往内科/心内科就诊", "reason": "多重心血管危险因素叠加", "target": "血压<130/80mmHg，LDL<2.6mmol/L"}
    ],
    "3_month_goals": ["戒烟或显著减量", "血压达标", "体重减少3-5kg"],
    "1_year_goals": ["血脂达标", "血糖控制在正常范围", "完成甲状腺结节随访"],
    "long_term_monitoring": ["每3个月查血压、血糖、血脂", "每年体检含肿瘤标志物"]
  },
  "personalized_advice": {
    "diet": ["地中海饮食模式", "减少红肉和加工肉类", "增加深海鱼类（每周2次）"],
    "exercise": "每周5次中等强度有氧运动（快步走/游泳），每次30-45分钟",
    "sleep_stress": "保证7-8小时睡眠，学习压力管理技巧",
    "smoking_alcohol": "强烈建议戒烟（最重要的单一干预），限酒至每周<2标准饮"
  },
  "specialist_referrals": [
    {"specialty": "心内科/内分泌科", "reason": "高血压合并多重代

_meta.json

{
  "ownerId": "kn7ft98qwhxyrgcy7b7rzdhrrd8366k6",
  "slug": "unisound-health-risk-assessment",
  "version": "1.0.2",
  "publishedAt": 1784188310763
}

skill-card.md

## Description:

Assesses health-exam reports across cardiovascular, glucose metabolism, tumor, metabolic syndrome, liver, kidney, and thyroid risk dimensions and produces a JSON risk profile plus a health risk report.

This skill is ready for commercial/non-commercial use.

## Publisher:

[unisound-llm](https://clawhub.ai/user/unisound-llm)

### License/Terms of Use:

MIT-0

## Use Case:

Health management teams and medical-service developers use this skill to assess de-identified health examination reports, classify major health risks, and draft time-bound management plans for qualified clinical review.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Sensitive medical-report content and API keys may be sent to a configurable remote LLM endpoint.

Mitigation: Use de-identified reports, keep the default trusted HTTPS endpoint unless an alternate endpoint is verified, and provide credentials through channels that do not expose them in shell history or logs.

Risk: Generated health recommendations can be incomplete, misleading, or clinically inappropriate.

Mitigation: Treat output as advisory health-risk support and require review by qualified medical professionals before patient-facing or care-management use.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/unisound-llm/skills/unisound-health-risk-assessment)
- [Publisher profile: unisound-llm](https://clawhub.ai/user/unisound-llm)
- [Unisound MaaS chat completions endpoint](https://maas-api.hivoice.cn/v1/chat/completions)

## Skill Output:

**Output Type(s):** [Text, JSON, Guidance]

**Output Format:** [JSON followed by a plain-text health risk report]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May be printed to stdout or saved to a file; requires a health-exam report input and an appkey.]

## Skill Version(s):

1.0.2 (source: server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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Machine-readable data

The same record, as JSON, for agents and crawlers.

{
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      "category": "vendor",
      "label": "Vendor",
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      "href": "https://clawhub.ai/unisound-llm/skills/unisound-health-risk-assessment",
      "sourceUrl": "https://clawhub.ai/unisound-llm/skills/unisound-health-risk-assessment",
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      "confidence": "medium",
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      "sourceType": "release",
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  ]
}

Record generated Oct 11, 2026.

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