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deepseek-extractDeepSeek 提取

Agent Skill

deepseek-extract 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。

总安装

2,913

周安装

119

GitHub Stars

公开资料未说明

下载量

942
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:deepseek-extract(DeepSeek 提取)
来源仓库:https://github.com/zz0116/deepseek-extract
安装命令:
openclaw skills install deepseek-extract
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 deepseek-extract

简介

从 DeepSeek 公开分享链接中提取完整对话历史,便于知识沉淀与二次分析。

  • 适用于还原 chat.deepseek.com/share/等 类型 URL 的原始问答记录。
  • 安装后粘贴 URL 即可自动解析并返回结构化对话内容,仅限公开链接可用。
  • 通过 clawhub 安装,需确认网络权限,私有会话无法提取。
  • 使用前请核实链接公开性及维护状态,避免因权限问题导致提取失败。

SKILL.md

name
deepseek-extract
description
>
version
1.0.0
context
fork
metadata
openclaw
emoji
📋
homepage
https://github.com/zz0116/deepseek-extract
requires
bins

DeepSeek Extract

Extract full conversation content from DeepSeek shared chat links.

Prerequisites

Before using this skill, ensure the following are installed:

pip install playwright
playwright install chromium

If playwright is not installed when the skill runs, inform the user and offer to run the install commands above.

Workflow

Step 1: Validate the URL

  1. Check if the provided URL matches https://chat.deepseek.com/share/...
  2. If the URL does not match this pattern, inform the user:

- "This skill only supports DeepSeek share links (chat.deepseek.com/share/...)." - If the URL is from another AI platform (ChatGPT, Claude, etc.), suggest the appropriate skill or manual copy.

  1. If valid, proceed to Step 2.

Step 2: Run the extraction script

Execute the extraction script from the skill's scripts/ directory:

python3 "<skill_dir>/scripts/extract_deepseek.py" "<share_url>" --output "<output_path>"

Parameters:

  • <share_url>: The DeepSeek share URL (required)
  • --output: Output file path (optional, defaults to ./deepseek_conversation.md)
  • --format: Output format — markdown (default) or json
  • --headed: Run browser in headed mode for debugging (optional flag)
  • --timeout: Page load timeout in milliseconds (optional, defaults to 30000)

Replace <skill_dir> with the actual skill base directory path.

Error handling:

  • If playwright is not installed: inform the user and offer to run pip install playwright && playwright install chromium
  • If python3 is not found: try python instead
  • If the script exits with a timeout error: retry with --timeout 60000
  • If the script exits with an empty extraction: try with --headed flag to debug visually

Step 3: Verify and deliver

  1. Read the output file to verify content was extracted successfully.
  2. If the output is empty or contains fewer than 2 messages:

- Try again with --headed flag for debugging - The DeepSeek page may have anti-bot protection — inform the user - Suggest: "DeepSeek may be blocking automated access. You can try manually copying the conversation."

  1. If content was extracted successfully, present it to the user.
  2. If the user wants a different format (Word, PDF, etc.), use other skills (docx, pdf) to convert.

Step 4: Cleanup

Remove any temporary files created during extraction. Keep the output file unless the user specifies otherwise.

How It Works

The extraction script uses Playwright (headless Chromium) to:

  1. Navigate to the DeepSeek share URL
  2. Wait for the SPA to fully render (JavaScript execution)
  3. Try multiple CSS selector strategies to find message elements
  4. Classify messages as user or assistant based on class names and data attributes
  5. If primary selectors fail, use aggressive text-parsing fallback
  6. Output the result as Markdown or JSON

Output Format

Markdown (default)

# DeepSeek 对话记录

> 来源: <share_url>

---

## 用户
<message content>

## DeepSeek
<response content>

---
(repeat for each turn)

JSON

{
  "url": "<share_url>",
  "title": "<page title>",
  "messages": [
    {"role": "user", "content": "..."},
    {"role": "assistant", "content": "..."}
  ]
}

Troubleshooting

IssueCauseSolution
No messages extractedAnti-bot / CAPTCHATry --headed flag; copy manually
Timeout errorSlow networkRetry with --timeout 60000
Incomplete contentLazy loadingScript auto-scrolls; try --headed to verify
playwright not foundNot installedRun pip install playwright && playwright install chromium
python3 not foundWindows environmentTry python instead of python3

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

77.05%
按下载量换算726

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。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。

来源信息

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