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health-records-ingest健康记录摄取

Agent Skill

health-records-ingest 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,206

周安装

177

GitHub Stars

公开资料未说明

下载量

1,473
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:health-records-ingest(健康记录摄取)
来源仓库:https://github.com/hsongra11/health-records-ingest
安装命令:
openclaw skills install health-records-ingest
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install health-records-ingest

简介

帮助用户构建个性化健康记录系统,支持目标设定与进度跟踪。

  • 适用于采访用户需求并生成定制化健康表单或问卷。
  • 可集成多种数据类型,便于后续分析和可视化展示。
  • 安装命令:openclaw skills install health-records-ingest。
  • 涉及用户隐私数据时需明确授权并限制访问范围。

SKILL.md

name
health-records-ingest
description
Interview a user and build a personalized health-record system around their goals, reports, and tracking needs. Use when someone wants to organize their health data, create a reusable health workspace, ingest PDFs/screenshots/scans, define what to track over time, and maintain a durable system with raw files, readable notes, structured data, and summaries.

Health Records Ingest

Build a personal health knowledge system around the user, not just around files.

Workflow

  1. Interview the user first.
  2. Confirm privacy, processing, and storage boundaries before touching files.
  3. Define the health workspace structure around their goals.
  4. Preserve incoming raw files.
  5. Create readable extractions.
  6. Add or update structured tracking files.
  7. Maintain dashboard/history summaries.
  8. Recheck unclear extractions without overwriting the original note.

Interview first

Before building the system, ask only the minimum useful questions needed to shape it.

Default interview topics:

  • What is the goal: baseline tracking, fitness transformation, disease management, annual records, or lab organization?
  • What file types will arrive: blood tests, scans, prescriptions, DEXA, wearables, Apple Health exports, doctor notes?
  • What should be tracked over time?
  • What summaries matter most: abnormalities, trends, doctor-ready summaries, supplements, symptoms, activity?
  • Does the user want a simple structure or a more detailed longitudinal system?
  • Should processing be strictly local? Default to local-only unless the user explicitly approves another path.
  • Are third-party OCR, cloud extraction, or web APIs allowed? Default to no external upload without explicit consent.
  • Where should files live, and what retention/deletion expectations does the user want?

If the user already provided enough context, do not over-interview. Start building.

Build the system around the user

Create the smallest useful system first, then expand.

Default folder layout:

health/
  reports/      # original PDFs
  scans/        # original images / photos
  notes/        # one extracted Markdown note per report
  data/         # JSON and CSV tracking files
  history/      # chronological summaries
  dashboard/    # latest snapshot + abnormalities summary

Adapt this when needed. Example additions:

  • health/prescriptions/
  • health/symptoms/
  • health/medicines/
  • health/doctors/
  • health/wearables/

Rules

  • Preserve raw sources.
  • Default to local-only processing.
  • Do not upload health files, screenshots, or extracted data to third-party OCR/API services unless the user explicitly approves it for this workflow.
  • If local extraction is incomplete, ask before using any cloud or external processing path.
  • Use date-first filenames where possible.
  • Keep one Markdown note per source report, plus *-recheck.md only when needed.
  • Use simple status labels such as in_range, low, high, reactive, pending.
  • Keep summaries traceable back to the original file path.
  • Be explicit about storage location and retention when setting up a new system.
  • Do not present extracted content as medical advice.
  • Prefer incremental updates over reorganizing everything repeatedly.

What to capture

Lab reports

  • test name
  • value
  • units
  • reference range if visible
  • status

Body composition

  • weight
  • body fat %
  • fat mass
  • muscle mass
  • BMI
  • visceral fat
  • water metrics if present
  • segmental breakdown if present

Imaging / ECG / scans

  • study type
  • impression / conclusion
  • notable numeric values
  • normal vs abnormal summary

Recheck behavior

If a PDF pass misses something but later screenshot/manual review confirms it:

  • create or update a *-recheck.md note
  • say exactly what changed
  • preserve the earlier extraction note

References

Read references/workflow.md for the full four-layer method, interview guidance, naming conventions, and update process. Read references/examples.md for concrete file examples and summary patterns.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

97.04%
按下载量换算1,429

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通过

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

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