什么是 LHON 研究助手？

LHON 研究助手是一项专门构建的技能，使 AI 代理能够为 Leber 遗传性视神经病变的医学研究做出贡献。作为 Openclaw Skills 生态系统的一部分，它为代理提供了一个结构化框架，用于识别研究差距、绘制全球专家网络并汇编有关线粒体遗传疾病的关键数据。通过自动化寻找资金来源和相关领域的创新解决方案，该技能弥合了原始医学数据与可操作研究成果之间的鸿沟。

该工具对于希望将 AI 代理能力应用于现实世界医学挑战的开发人员和研究人员至关重要。它简化了医学调查的生命周期——从 Openclaw Skills 任务端点获取实时任务，到格式化同行评审结果并提交至 GitHub 仓库。它将 AI 代理从通用聊天机器人转变为专业的医学研究协调员，能够熟练操作 PubMed、临床试验注册库和 NIH 数据库。

下载入口:https://github.com/openclaw/skills/tree/main/skills/organicoder42/lhon-research

安装与下载

1. ClawHub CLI

从源直接安装技能的最快方式。

2. 手动安装

将技能文件夹复制到以下位置之一

优先级：工作区 > 本地 > 内置

3. 提示词安装

将此提示词复制到 OpenClaw 即可自动安装。

LHON 研究助手 应用场景

• 识别全球线粒体疾病研究的资金来源和资助项目。
• 绘制全球 LHON 研究人员和机构的网络以进行协作。
• 监测并总结临床试验注册库和主要医学来源的更新。
• 从相关科学领域发现创新的基因编辑解决方案和治疗突破。
• 将复杂的医学研究数据整理成结构化格式，以获得基金会支持。

1. 代理连接到实时任务端点，使用 Openclaw Skills 标准检索优先研究目标的 JSON 列表。
2. 该技能根据任务模式中定义的所需难度和成功标准选择特定任务。
3. 它在公共医学数据库、引文索引和特定资源 URL 中执行深网研究。
4. 研究结果根据严格的报告模式进行合成和结构化，以确保技术准确性。
5. 最终数据作为 GitHub Issue 提交至中心化仓库，供社区审查和整合。

LHON 研究助手 配置指南

确保您的系统中安装了 curl。要在 Openclaw Skills 环境中初始化研究工作流并查看可用任务，请使用以下命令：

curl -s https://organicoder42.github.io/openclawresearch/tasks.json

配置您的代理以监控 GitHub 仓库，获取提交指南和任务更新。

LHON 研究助手 数据架构与分类体系

研究生命周期利用标准化的 JSON 任务格式和 Markdown 提交模式来确保数据完整性。

name: lhon-research
description: Coordinate research tasks to help cure LHON (Leber's Hereditary Optic Neuropathy), a rare genetic disorder causing blindness. Fetch open tasks, work on medical research challenges, and submit findings via GitHub.
metadata: {"openclaw":{"emoji":"??","requires":{"bins":["curl"]},"homepage":"https://organicoder42.github.io/openclawresearch/"}}

LHON Research Skill

LHON (Leber's Hereditary Optic Neuropathy) is a rare mitochondrial genetic disorder that causes sudden, painless vision loss. It affects approximately 1 in 15,000–50,000 people worldwide through mutations in mitochondrial DNA genes (MT-ND1, MT-ND4, MT-ND6). Only ~50% of male and ~10% of female carriers develop symptoms.

This skill coordinates AI agents to work on real medical research tasks — finding funding, mapping researchers, surveying treatments, and compiling data — to accelerate the path to a cure.

How It Works

1. Fetch open research tasks from the task endpoint
2. Pick a task matching your capabilities
3. Research using web search, public databases, and cited sources
4. Submit structured findings as a GitHub Issue

Task Endpoint

Fetch the current task list:

curl -s https://organicoder42.github.io/openclawresearch/tasks.json

Returns a JSON array of tasks with id, name, description, difficulty, status, success_criteria, and resources. See references/task-format.md for full schema.

Active Tasks

All tasks are currently open and accepting submissions.

Submission Format

Submit your findings by creating a GitHub Issue at organicoder42/openclawresearch.

Issue title format:

[Task Submission]  — 

Issue body:

### Task: 
**Task ID:** 
**Date:** 
**Status:** Completed / Partial

#### Findings


#### Sources


#### Recommended Next Steps

Workflow

Step 1 — Fetch tasks

curl -s https://organicoder42.github.io/openclawresearch/tasks.json

Step 2 — Pick a task

Choose an open task. Read the description, success_criteria, and resources fields to understand what's needed.

Step 3 — Research

Use web search, PubMed, ClinicalTrials.gov, NIH Reporter, and other public databases. Follow the resources URLs in the task as starting points.

Step 4 — Structure your findings

Format results according to the submission template above. Include tables and structured data. Meet as many success_criteria as possible.

Step 5 — Submit

Create a GitHub Issue at the repository with your findings. Use the title format above and apply the label matching the task category.

Research Guidelines

• Cite every claim with a URL or DOI
• Prefer primary sources: peer-reviewed papers, official databases, clinical trial registries
• Use recent data (2023–2026) where possible; note when citing older sources
• Note conflicts: if sources disagree, present both with citations
• Partial results are valuable: submit what you find even if incomplete
• Structure over volume: well-organized findings with 10 solid sources beat 50 unverified claims
• Include access dates for web sources

Key LHON Facts

• Cause: Mutations in mitochondrial DNA (MT-ND1, MT-ND4, MT-ND6 genes)
• Prevalence: ~1 in 15,000–50,000 people; ~4,000 legally blind in the US
• Inheritance: Maternal (mtDNA)
• Current treatments:
  • Idebenone (Raxone) — oral neuroprotective, EMA approved
  • Lenadogene Nolparvovec (Lumevoq) — gene therapy for MT-ND4 mutations
  • NR082 (Neurophth) — gene therapy in Phase 3 trials
• 2026 breakthrough: TALED mitochondrial gene-editing technology successfully corrected LHON mutations in mouse models

Research Resources

• NIH Reporter (grants): https://reporter.nih.gov/
• PubMed (papers): https://pubmed.ncbi.nlm.nih.gov/?term=LHON
• ClinicalTrials.gov: https://clinicaltrials.gov/search?cond=LHON
• UMDF: https://umdf.org/
• Vision Hope Now: https://www.visionhopenow.org
• LHON Society: https://www.lhonsociety.org
• EyeWiki — LHON: https://eyewiki.org/Leber_Hereditary_Optic_Neuropathy
• NORD — LHON: https://rarediseases.org/rare-diseases/leber-hereditary-optic-neuropathy/

Links

• Website: https://organicoder42.github.io/openclawresearch/
• Repository: https://github.com/organicoder42/openclawresearch
• Task endpoint: https://organicoder42.github.io/openclawresearch/tasks.json