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Agent Skill · 研究检索

lab-result-interpretation(实验室结果解释)

lab-result-interpretation 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

lab-result-interpretation 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为只读;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 27,187。

总安装 3,432周安装 143GitHub Stars 公开资料未说明下载 1,144核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:lab-result-interpretation(实验室结果解释)
来源仓库:https://github.com/aipoch-ai/lab-result-interpretation
安装命令:
openclaw skills install lab-result-interpretation
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 lab-result-interpretation

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

一种医疗辅助工具,可将复杂的生化实验室测试结果转化为清晰、患者友好的解释,并附有安全免责声明和安全说明。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install lab-result-interpretation;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

lab-result-interpretation 怎么安装?

在终端执行 openclaw skills install lab-result-interpretation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

lab-result-interpretation 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

lab-result-interpretation 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

lab-result-interpretation 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

lab-result-interpretation 用的人多吗?

公开数据是累计安装 3,432 次,近一周安装 143 次,下载 1,144 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

lab-result-interpretation 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
lab-result-interpretation

实验室结果解释 · 本页

3,432—只读MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
lab-result-interpretation
description
A medical assistant tool that transforms complex biochemical laboratory test results into clear, patient-friendly explanations with safety disclaimers and severity flags.
license
MIT
skill-author
AIPOCH

Lab Result Interpretation

A medical assistant tool that transforms complex biochemical laboratory test results into clear, patient-friendly explanations.

Quick Check

python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py --interactive

When to Use

  • Use this skill to interpret biochemical lab test results and generate patient-friendly explanations.
  • Use this skill to flag abnormal values with severity indicators and contextual health recommendations.
  • Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format.
  • Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Workflow

  1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
  2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
  3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
  4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
  5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Critical values: When any value is in the critical range, output a Critical Findings Summary block at the top of the response before the per-test breakdown. Sort findings by severity (critical → high → normal). Include an explicit urgent care recommendation for critical values.

Features

  • Parses various lab test formats (numeric values, units, reference ranges)
  • Compares values against standard reference ranges
  • Generates patient-friendly explanations
  • Flags abnormal values with severity indicators (critical → high → normal order)
  • Provides contextual health recommendations
  • Includes mandatory medical disclaimer in all outputs

Supported Test Types

CategoryTests
Blood RoutineWBC, RBC, Hemoglobin, Platelets, Hematocrit
Lipid PanelTotal Cholesterol, LDL, HDL, Triglycerides
Liver FunctionALT, AST, ALP, GGT, Bilirubin, Total Protein, Albumin
Kidney FunctionCreatinine, BUN, eGFR, Uric Acid
Blood SugarFasting Glucose, HbA1c
ThyroidTSH, T3, T4, FT3, FT4
ElectrolytesSodium, Potassium, Chloride, Calcium, Magnesium
InflammationCRP, ESR

Usage

As Module

from scripts.main import LabResultInterpreter

interpreter = LabResultInterpreter()
result = interpreter.interpret("Total Cholesterol: 5.8 mmol/L (Reference: 3.1-5.7)")
print(result.explanation)

CLI

python scripts/main.py --file lab_report.txt
python scripts/main.py --interactive

Parameters

NameTypeDefaultRequiredDescription
filestring""NoPath to lab report file to process
interactivebooleanfalseNoEnable interactive mode for manual input
inputstring""NoDirect lab test input string for interpretation

Input Format

Accepts flexible formats:

Test Name: Value Unit (Reference: Min-Max)
Test Name Value Unit Ref: Min-Max
Test Name: Value (Min-Max)

Output Format

{
  "test_name": "Total Cholesterol",
  "value": 5.8,
  "unit": "mmol/L",
  "reference_min": 3.1,
  "reference_max": 5.7,
  "status": "high",
  "explanation": "Your total cholesterol is slightly above the normal range...",
  "severity": "mild",
  "recommendation": "Consider reducing saturated fat intake..."
}

Medical Disclaimer

This tool provides educational information only and is not a substitute for professional medical advice, diagnosis, or treatment. Always consult with a qualified healthcare provider for interpretation of lab results. This tool does not diagnose — it only explains test meanings.

References

  • references/lab_reference_ranges.json — Standard reference ranges
  • references/explanation_templates.json — Patient-friendly templates
  • references/test_metadata.json — Test descriptions and clinical notes

Dependencies

  • Python >= 3.8 (strictly required; dataclasses module used)
  • Runtime version guard: The script must check sys.version_info >= (3, 8) at startup and exit with 'Error: Python 3.8+ required' if the check fails, before any imports.

Prerequisites

pip install -r requirements.txt

Input Validation

This skill accepts: biochemical laboratory test results in standard formats (test name, value, unit, reference range) for the purpose of generating patient-friendly explanations.

If the user's request does not involve lab result interpretation — for example, asking to diagnose a condition, prescribe treatment, interpret imaging results, or perform general medical consultation — do not proceed with the workflow. Instead respond:

"lab-result-interpretation is designed to explain biochemical lab test values in patient-friendly language. It does not diagnose conditions or replace medical advice. Your request appears to be outside this scope. Please provide lab test values with reference ranges, or consult a qualified healthcare provider."

Do not continue the workflow when the request is out of scope, missing lab values, or would require clinical diagnosis. For missing inputs, state exactly which fields are missing.

Fallback Behavior

If scripts/main.py fails or required inputs are incomplete:

  1. Report the exact failure point and error message.
  2. State what can still be completed (e.g., partial interpretation of available values).
  3. Manual fallback: use --interactive mode to enter values one at a time, or provide the raw value and reference range for manual comparison.
  4. Do not fabricate lab values, reference ranges, or clinical interpretations.

Boundary Enforcement

This skill explicitly does not:

  • Diagnose medical conditions
  • Recommend specific medications or dosages
  • Replace consultation with a licensed healthcare provider
  • Interpret imaging, pathology, or genetic test results (for imaging results, consult a radiologist report; for genetic tests, consult a genetic counselor)

Any request that would require crossing these boundaries must be declined with the medical disclaimer and a referral to appropriate professional resources.

Output Requirements

Every final response must make these items explicit when relevant:

  • Objective or requested deliverable
  • Inputs used and assumptions introduced
  • Workflow or decision path
  • Critical Findings Summary (if any value is critical — placed at top, before per-test breakdown)
  • Core result, recommendation, or artifact
  • Constraints, risks, caveats, or validation needs (including medical disclaimer)
  • Unresolved items and next-step checks

Error Handling

  • If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
  • If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
  • If scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
  • If the --file path contains ../ or points outside the workspace, reject with a path traversal warning before opening the file.
  • Do not fabricate files, citations, data, search results, or execution outcomes.

Response Template

Use the following fixed structure for non-trivial requests:

  1. Objective
  2. Inputs Received
  3. Assumptions
  4. Workflow
  5. Critical Findings Summary (if applicable — urgent care recommendation for critical values)
  6. Deliverable
  7. Risks and Limits (always include medical disclaimer)
  8. Next Checks

For stress/multi-constraint requests, also include:

  • Constraints checklist (compliance, performance, error paths)
  • Explicit boundary statement confirming no diagnosis was made
  • Unresolved items with explicit blocking reasons

If the request is simple, you may compress the structure, but always keep the medical disclaimer and scope limits explicit.

平台分布

OpenClaw

93.26%
按下载量换算1,067

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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