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Agent Skill · 研究检索

chat-lift(聊天电梯)

chat-lift 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。

chat-lift 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,091。

总安装 9,694周安装 396GitHub Stars 公开资料未说明下载 3,105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
1.0.1

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:chat-lift(聊天电梯)
来源仓库:https://github.com/theshadowrose/chat-lift
安装命令:
openclaw skills install chat-lift
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 chat-lift

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。

从 ChatGPT、Claude 和 Gemini 导入、搜索和存档 AI 对话。干净的索引格式、全文搜索、静态 HTML 存档。无需服务器。

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 chat-lift;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

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

chat-lift 怎么安装?

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

chat-lift 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。

chat-lift 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

chat-lift 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。

chat-lift 用的人多吗?

公开数据是累计安装 9,694 次,近一周安装 396 次,下载 3,105 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。

chat-lift 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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
chat-lift

聊天电梯 · 本页

9,694—操作浏览器MIT-0通过

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
ChatLift AI Conversation Exporter & Archive
description
Import, search, and archive AI conversations from ChatGPT, Claude, and Gemini. Clean indexed formats, full-text search, static HTML archive. No server required.
author
@TheShadowRose
version
1.0.1
tags
["export", "archive", "conversations", "search", "chatgpt", "claude", "backup"]
license
MIT

ChatLift AI Conversation Exporter & Archive

Import, search, and archive AI conversations from ChatGPT, Claude, and Gemini. Clean indexed formats, full-text search, static HTML archive. No server required.


Import, search, and archive your AI conversations.

Extract ChatGPT, Claude, and Gemini conversation exports into clean, indexed formats. Full-text search. Static HTML archive with search bar. No server required.


What It Does

ChatLift converts AI conversation exports into portable, searchable formats:

  1. Import - Parse ChatGPT/Claude/Gemini exports
  2. Convert - Generate Markdown, HTML, and JSON
  3. Search - Full-text search across all conversations
  4. Archive - Static HTML archive with navigation

Why This Exists

AI chat platforms:

  • Lock your conversations in proprietary formats
  • Make search difficult or impossible
  • Can delete your data at any time

ChatLift gives you control:

  • Own your conversation history
  • Search across all platforms
  • Portable formats (Markdown, HTML, JSON)
  • Works offline forever

Quick Start

Install

No dependencies! Python 3.7+ stdlib only.

# Copy config (optional)
cp config_example.py config.py

Import Conversations

Export your conversations from ChatGPT, Claude, or Gemini, then:

# Import ChatGPT export
python3 chat_lift.py chatgpt conversations.json

# Import Claude export
python3 chat_lift.py claude claude-export.json

# Import Gemini export
python3 chat_lift.py gemini gemini-conversations.json

Generates:

  • chat-archive/markdown/*.md - Human-readable markdown
  • chat-archive/html/*.html - Styled HTML pages
  • chat-archive/json/*.json - Structured JSON

Search Conversations

# Search all conversations
python3 chat_search.py search --query "machine learning"

# Search with regex
python3 chat_search.py search --query "python.*async" --regex

# Search by date range
python3 chat_search.py date --start-date 2026-01-01 --end-date 2026-02-01

# Get archive statistics
python3 chat_search.py stats

Generate HTML Archive

# Generate static archive website
python3 chat_archive.py

# Open chat-archive/web/index.html in browser

The HTML archive includes:

  • Search bar - Filter by keyword or source
  • Navigation - Browse all conversations
  • No server needed - Pure static files

Usage Examples

Import Multiple Exports

# Import all your platforms
python3 chat_lift.py chatgpt chatgpt-export.json
python3 chat_lift.py claude claude-export.json
python3 chat_lift.py gemini gemini-export.json

# Generate unified archive
python3 chat_archive.py

Search Across All Platforms

from chat_search import ConversationSearcher

searcher = ConversationSearcher('chat-archive')

# Find all conversations mentioning "agent"
results = searcher.search('agent')

for result in results:
    print(f"{result['conversation']['title']}")
    print(f"  Source: {result['conversation']['source']}")
    print(f"  Matches: {result['total_matches']}\
")

Custom Output Formats

# Only generate markdown
python3 chat_lift.py chatgpt export.json --formats markdown

# Generate all formats
python3 chat_lift.py chatgpt export.json --formats markdown html json

# Custom output directory
python3 chat_lift.py chatgpt export.json --output-dir ~/my-chats

Filter Search Results

# Search only ChatGPT conversations
python3 chat_search.py search --query "python" --source chatgpt

# Search only user messages
python3 chat_search.py search --query "explain" --role user

# Case-sensitive search
python3 chat_search.py search --query "API" --case-sensitive

Export Instructions

ChatGPT

  1. Go to chat.openai.com
  2. Settings → Data controls → Export data
  3. Wait for email with download link
  4. Download conversations.json

Claude

  1. Go to claude.ai
  2. Settings → Privacy → Export your data
  3. Download export file
  4. Extract JSON from archive

Gemini

  1. Go to gemini.google.com
  2. Account settings → Download your data
  3. Select Gemini conversations
  4. Download export file

File Formats

Markdown

# Conversation Title

**Source:** chatgpt  
**ID:** abc123def456  
**Created:** 2026-02-21 10:30:00  

---

## USER

How do I deploy a Flask app?

*2026-02-21 10:30:15*

---

## ASSISTANT

Here's how to deploy a Flask application...

*2026-02-21 10:30:45*

---

JSON

{
  "id": "abc123def456",
  "title": "Conversation Title",
  "source": "chatgpt",
  "create_time": 1708512600,
  "messages": [
    {
      "role": "user",
      "content": "How do I deploy a Flask app?",
      "timestamp": 1708512615
    },
    {
      "role": "assistant",
      "content": "Here's how to deploy a Flask application...",
      "timestamp": 1708512645
    }
  ]
}

HTML

Clean, styled HTML with:

  • Responsive design
  • Color-coded messages
  • Timestamps
  • Source badges

Archive Structure

chat-archive/
├── markdown/          # Human-readable markdown
│   ├── abc123.md
│   └── def456.md
├── html/              # Styled HTML pages
│   ├── abc123.html
│   └── def456.html
├── json/              # Structured JSON
│   ├── abc123.json
│   └── def456.json
└── web/               # Static HTML archive
    ├── index.html     # Browse/search interface
    ├── abc123.html    # Conversation pages
    ├── def456.html
    ├── style.css      # Styling
    └── search.js      # Search functionality

Search Features

Full-Text Search

# Simple text search
python3 chat_search.py search --query "machine learning"

# Case-sensitive
python3 chat_search.py search --query "API" --case-sensitive

# Regex patterns
python3 chat_search.py search --query "python.*async" --regex

Filters

# Filter by source platform
python3 chat_search.py search --query "code" --source chatgpt

# Filter by message role
python3 chat_search.py search --query "explain" --role assistant

# Combine filters
python3 chat_search.py search --query "deploy" --source claude --role user

Date Range

# Conversations from specific date range
python3 chat_search.py date --start-date 2026-01-01 --end-date 2026-02-01

# All conversations after date
python3 chat_search.py date --start-date 2026-02-01

# All conversations before date
python3 chat_search.py date --end-date 2026-02-01

Statistics

python3 chat_search.py stats

Shows:

  • Total conversations
  • Total messages
  • Word count
  • Breakdown by source
  • Breakdown by role

HTML Archive

Features

  • Search bar - Real-time filter as you type
  • Source filter - Filter by ChatGPT, Claude, Gemini
  • Clean design - Responsive, mobile-friendly
  • No server - Pure static HTML/CSS/JS
  • Works offline - Archive travels with you

Customization

Edit chat-archive/web/style.css to customize:

  • Colors
  • Fonts
  • Layout
  • Message styling

The archive is pure HTML/CSS/JS - modify freely.


Integration

Python API

from chat_lift import ConversationImporter
from chat_search import ConversationSearcher
from chat_archive import ArchiveGenerator

# Import conversations
importer = ConversationImporter('chat-archive')
conversations = importer.import_chatgpt('export.json')

for conv in conversations:
    importer.save_conversation(conv, formats=['markdown', 'json'])

# Search
searcher = ConversationSearcher('chat-archive')
results = searcher.search('python programming')

# Generate HTML archive
generator = ArchiveGenerator('chat-archive')
generator.generate_archive()

Batch Processing

import glob
from chat_lift import ConversationImporter

importer = ConversationImporter('chat-archive')

# Import all ChatGPT exports in directory
for export_file in glob.glob('exports/chatgpt-*.json'):
    conversations = importer.import_chatgpt(export_file)
    for conv in conversations:
        importer.save_conversation(conv)

print("All exports imported!")

Limitations

See LIMITATIONS.md for details.

Key constraints:

  • Export formats vary by platform version
  • No real-time sync (manual export/import)
  • Search is text-based (not semantic)
  • Large archives (10,000+ conversations) may be slow

License

MIT License - See LICENSE

Author: Shadow Rose


Why This Exists

Your AI conversations are valuable:

  • Learning history
  • Project documentation
  • Personal knowledge base

But they're locked in proprietary platforms that:

  • Can change or delete your data
  • Make search difficult
  • Don't export cleanly

ChatLift gives you:

  • Ownership - Your data, your formats
  • Portability - Markdown, HTML, JSON
  • Search - Find anything instantly
  • Permanence - Works offline forever

Take back your conversation history.


⚠️ Disclaimer

This software is provided "AS IS", without warranty of any kind, express or implied.

USE AT YOUR OWN RISK.

  • The author(s) are NOT liable for any damages, losses, or consequences arising from

the use or misuse of this software — including but not limited to financial loss, data loss, security breaches, business interruption, or any indirect/consequential damages.

  • This software does NOT constitute financial, legal, trading, or professional advice.
  • Users are solely responsible for evaluating whether this software is suitable for

their use case, environment, and risk tolerance.

  • No guarantee is made regarding accuracy, reliability, completeness, or fitness

for any particular purpose.

  • The author(s) are not responsible for how third parties use, modify, or distribute

this software after purchase.

By downloading, installing, or using this software, you acknowledge that you have read this disclaimer and agree to use the software entirely at your own risk.

DATA DISCLAIMER: This software processes and stores data locally on your system. The author(s) are not responsible for data loss, corruption, or unauthorized access resulting from software bugs, system failures, or user error. Always maintain independent backups of important data. This software does not transmit data externally unless explicitly configured by the user.


Support & Links

🐛 Bug ReportsTheShadowyRose@proton.me
☕ Ko-fiko-fi.com/theshadowrose
🛒 Gumroadshadowyrose.gumroad.com
🐦 Twitter@TheShadowyRose
🐙 GitHubgithub.com/TheShadowRose
🧠 PromptBasepromptbase.com/profile/shadowrose

*Built with OpenClaw — thank you for making this possible.*


🛠️ Need something custom? Custom OpenClaw agents & skills starting at $500. If you can describe it, I can build it. → Hire me on Fiverr

平台分布

OpenClaw

78.05%
按下载量换算2,423

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。目前只有一个公开来源,建议同时核对源仓库。

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