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unisound-llm

unisound-med-knowledge-qa

by Unisound-LLM · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install unisound-med-knowledge-qa
Description
医学考试、专科问答、文献阅读理解、名词规范解释与术语同义匹配等知识问答。由调用方传入题目,经内部医疗大模型作答;通过 --task 选择具体场景提示词;仅含 `scripts/run.py`,可独立拷贝部署。
README (SKILL.md)

医学知识与专科问答

概述

覆盖医学知识检索、理解与规范表述类问答,依赖医疗大模型专业能力,按任务类型切换提示词。

具体场景通过 --task 切换系统提示词(见下表),能力依赖内部医疗大模型;集成方也可通过 --system-prompt 完全自定义。

--task 能力
exam 医学考试单项选择题
lit-qa 医学文献阅读理解问答
spe-qa 医学专科问答
synonym 医学术语同义匹配
term 医学名词规范解释

本能力与具体业务请求解耦:平台或调用方如何组织用户输入由集成方决定;此处只约定如何把题目交给脚本(见下)。

题目输入(三选一)

  1. --question:直接传入完整题干字符串。
  2. --input PATH
    • .jsonl:每行一个 JSON 对象,须含非空字符串字段 question;可用 --index / --batch / --match-id 选取记录;
    • .json:单个对象,须含 question
    • 其他扩展名:按 UTF-8 纯文本整文件作为题干。
    • - 时从 stdin 读取一条 JSON(含 question)或纯文本。
  3. stdin(且未传 --question / --input、且 stdin 非 TTY):读入 JSON 对象或纯文本,规则同 -

可在 JSON 的 other.task 中指定任务类型(与 --task 等价;命令行 --task 优先)。

模型

  • 默认 u1-insuremed,接口 https://maas-api.hivoice.cn/v1/chat/completions(可通过参数覆盖)。

用法示例

# 指定任务类型与题干
python3 scripts/run.py --task exam --question "题干……" --appkey YOUR_KEY

# 从 jsonl 取题(other.task 可省略若命令行已传 --task)
python3 scripts/run.py --task exam --input /path/to/items.jsonl --index 0 --appkey YOUR_KEY

参数

  • --task必填(除非 other.task 已给出)。见上表。
  • --question / --input:见上,与 stdin 三选一(--question--input 不可同时使用)。
  • --appkey STRING必填--dry-run 时除外)。内部医疗大模型鉴权 key。
  • --index--match-id--batch:仅对 .jsonl 生效。
  • --dry-run:不调用模型,仅输出解析后的题目 JSON。
  • --model--api-url--temperature--timeout--system-prompt:调模型参数。
  • --output PATH:另存完整 JSON(批量为 NDJSON)。
  • --text-only:标准输出仅打印模型答案文本。

输出

默认可解析 JSON:含 statustasktask_titlequestionanswerrecord_indexmetamodelinput_modeinput_path 等;skill 为本 skill 标题。

合规说明

输出为模型辅助信息,不构成正式诊疗决策;涉及真实患者数据须先脱敏并遵守院内流程。

Usage Guidance
Treat this as an incomplete low-confidence review; install only after the actual SKILL.md, metadata, install spec, manifest, and included files are reviewed.
Capability Assessment
Purpose & Capability
No artifact evidence was available to support a purpose or capability concern.
Instruction Scope
No artifact evidence was available to support an instruction-scope concern.
Install Mechanism
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Credentials
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Persistence & Privilege
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How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install unisound-med-knowledge-qa
  3. After installation, invoke the skill by name or use /unisound-med-knowledge-qa
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
med-llm-knowledge-qa v1.0.0 — Initial Release - Provides medical exam, specialty Q&A, literature comprehension, terminology explanations, and synonym matching via an internal medical LLM. - Supports task-specific prompts using --task for flexible scenario switching. - Accepts questions via command line, input file (including .jsonl/.json/text), or stdin. - Outputs structured JSON with model responses and meta info; offers text-only mode. - Allows full control of LLM parameters (model, API URL, temperature, etc.). - Clearly states compliance/disclaimer requirements for sensitive data.
Metadata
Slug unisound-med-knowledge-qa
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is unisound-med-knowledge-qa?

医学考试、专科问答、文献阅读理解、名词规范解释与术语同义匹配等知识问答。由调用方传入题目,经内部医疗大模型作答;通过 --task 选择具体场景提示词;仅含 `scripts/run.py`,可独立拷贝部署。 It is an AI Agent Skill for Claude Code / OpenClaw, with 113 downloads so far.

How do I install unisound-med-knowledge-qa?

Run "/install unisound-med-knowledge-qa" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is unisound-med-knowledge-qa free?

Yes, unisound-med-knowledge-qa is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does unisound-med-knowledge-qa support?

unisound-med-knowledge-qa is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created unisound-med-knowledge-qa?

It is built and maintained by Unisound-LLM (@unisound-llm); the current version is v1.0.0.

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