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数据映射与队列分析 (Agentic AI 科研平台)
作者
EmergencerOnEarth
· GitHub ↗
· v0.1.0
· MIT-0
114
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在 OpenClaw 中安装
/install agentic-cohort-analyst
功能描述
将研究变量映射到院内数据字典,评估 Cohort 可行性(候选样本量、缺失率、风险提示),并生成纳排标准草案。当用户需要做数据映射或队列可行性分析时触发。
使用说明 (SKILL.md)
数据映射与队列分析 Skill
何时使用
当用户需要单独执行数据映射或队列可行性分析时使用,例如:
- 「帮我看看院内有哪些可用变量」
- 「做一下 Cohort 可行性评估」
- 「生成纳排标准」
如果是完整任务流程的一部分,则由 task-planner 调度。
执行步骤
1. 上报开始
curl -s -X POST http://localhost:5001/api/report \
-H "Content-Type: application/json" \
-d '{"skill":"cohort-analyst","display_name":"数据映射与队列分析","status":"running","message":"正在连接院内数据字典,匹配变量与评估缺失率..."}'
2. 读取数据并输出
读取 /home/ubuntu/workspace/demo/mock_data/cohort.json,向用户展示:
- 变量映射表(表格形式):研究变量、院内字段名、数据源、可用性、缺失率
- Cohort 概览:候选病例数、时间范围、高质量/中等/高缺失变量计数
- 风险提示:逐条列出风险等级、问题项、建议
- 纳排标准草案:纳入标准和排除标准分别列出
- 分组预览:如果数据中有
group_preview,展示各方案的样本量
3. 上报完成
curl -s -X POST http://localhost:5001/api/report \
-H "Content-Type: application/json" \
-d '{"skill":"cohort-analyst","display_name":"数据映射与队列分析","status":"completed","message":"已完成 9 个变量映射,候选队列 1,284 例"}'
安全使用建议
This skill is internally consistent for doing a demo cohort mapping: it reads a local demo JSON and reports status to a local HTTP endpoint. Before installing/using it, confirm (1) the referenced file path (/home/ubuntu/workspace/demo/mock_data/cohort.json) is the intended dataset (avoid pointing to real patient data unless you trust the skill and environment), (2) the reporting endpoint (http://localhost:5001) is a trusted local service and not a tunnel to an external party, and (3) run the skill in an isolated/test environment first. If you need it to operate on your real institutional data, update the instructions to point to your authorized data source and verify logging/retention policies. If anything about the hard-coded path or the localhost endpoint is unexpected, treat that as a red flag and ask the skill author to remove or parameterize those values.
功能分析
Type: OpenClaw Skill
Name: agentic-cohort-analyst
Version: 0.1.0
The skill bundle is designed for medical cohort analysis and data mapping. It reads a local data file (/home/ubuntu/workspace/demo/mock_data/cohort.json) and uses curl to report status updates to a local API endpoint (http://localhost:5001/api/report). The instructions in SKILL.md are consistent with the stated purpose, and there are no signs of data exfiltration, malicious execution, or prompt injection attacks.
能力评估
Purpose & Capability
The skill promises to map research variables to an institutional data dictionary and evaluate cohort feasibility; the SKILL.md instructs reading a cohort JSON and producing mapping, cohort overview, risk notes and inclusion/exclusion drafts — these are coherent with the stated purpose.
Instruction Scope
The runtime instructions explicitly read a local file (/home/ubuntu/workspace/demo/mock_data/cohort.json) and make HTTP POSTs to http://localhost:5001/api/report. Reading a local cohort file and reporting progress is within scope, but the file path and the local report endpoint are hard-coded and not declared elsewhere; confirm these targets are intended and safe in your environment.
Install Mechanism
There is no install spec and no code files (instruction-only skill), which is the lowest-risk modality — nothing is written to disk by an installer.
Credentials
The skill requests no environment variables or external credentials. However, it does access a specific local filesystem path and a localhost HTTP endpoint; while these are functionally related to the skill's task, you should verify that the file and endpoint contain only intended test/demo data and that posting to localhost is safe.
Persistence & Privilege
The skill is not always-enabled and does not request persistent privileges or modify other skills or system-wide settings.
如何使用
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install agentic-cohort-analyst - 安装完成后,直接呼叫该 Skill 的名称或使用
/agentic-cohort-analyst触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
initial publish
元数据
常见问题
数据映射与队列分析 (Agentic AI 科研平台) 是什么?
将研究变量映射到院内数据字典,评估 Cohort 可行性(候选样本量、缺失率、风险提示),并生成纳排标准草案。当用户需要做数据映射或队列可行性分析时触发。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 114 次。
如何安装 数据映射与队列分析 (Agentic AI 科研平台)?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install agentic-cohort-analyst」即可一键安装,无需额外配置。
数据映射与队列分析 (Agentic AI 科研平台) 是免费的吗?
是的,数据映射与队列分析 (Agentic AI 科研平台) 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
数据映射与队列分析 (Agentic AI 科研平台) 支持哪些平台?
数据映射与队列分析 (Agentic AI 科研平台) 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 数据映射与队列分析 (Agentic AI 科研平台)?
由 EmergencerOnEarth(@emergenceronearth)开发并维护,当前版本 v0.1.0。
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