zeelin-deep-research

调用Zeelin Deep Research API进行深度研究任务。完全异步处理:提交任务后立即返回,后台进程自动确认大纲并定时检查任务状态,任务完成后自动保存md文件。自动配置定时通知(每2分钟检查),任务完成后主动通知用户。使用前必须先询问用户思考模式和搜索范围。

3,891 stars

Best use case

zeelin-deep-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

调用Zeelin Deep Research API进行深度研究任务。完全异步处理:提交任务后立即返回,后台进程自动确认大纲并定时检查任务状态,任务完成后自动保存md文件。自动配置定时通知(每2分钟检查),任务完成后主动通知用户。使用前必须先询问用户思考模式和搜索范围。

Teams using zeelin-deep-research should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/desearch-skill/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/angelandpeiqi/desearch-skill/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/desearch-skill/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How zeelin-deep-research Compares

Feature / Agentzeelin-deep-researchStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

调用Zeelin Deep Research API进行深度研究任务。完全异步处理:提交任务后立即返回,后台进程自动确认大纲并定时检查任务状态,任务完成后自动保存md文件。自动配置定时通知(每2分钟检查),任务完成后主动通知用户。使用前必须先询问用户思考模式和搜索范围。

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Zeelin Deep Research Skill

本skill用于调用Zeelin Deep Research API执行深度研究任务,采用完全异步处理模式。

## ⚠️ 重要:使用前必须先询问用户

当用户要求进行研究任务时,**必须先询问以下信息**:

1. **思考模式**(必选):
   | 模式 | 说明 | 适用场景 |
   |------|------|----------|
   | smart | 普通模式 | 快速简单的问题 |
   | deep | 深度模式 (~5000字) | 论文、竞品调研、中度报告 |
   | major | 专家模式 (~10000+字) | 深度研究报告 |

2. **搜索范围**(必选):
   | 范围 | 说明 |
   |------|------|
   | web | 全网搜索 |
   | academic | 学术搜索 |
   | selected | 精选 |

3. **研究主题**(必选):用户想要研究的具体问题

## 配置 API Key

### 方式1:命令行设置(推荐)
```bash
python3 scripts/async_runner.py --set-key "YOUR_API_KEY"
```

### 方式2:配置文件
```bash
echo '{"api_key": "YOUR_API_KEY"}' > ~/.openclaw/zeelin-config.json
```

获取 API Key:https://desearch.zeelin.cn

## 使用方法

### 1. 检查 API Key
```bash
python3 scripts/async_runner.py --check-key
```

### 2. 提交任务
```bash
cd ~/.openclaw/workspace/skills/zeelin-deep-research
python3 scripts/async_runner.py -q "研究主题" -t deep -sr web
```

## 功能特性

1. **异步提交**:提交任务后立即返回,不阻塞
2. **自动确认大纲**:后台进程自动调用 confirmOutline
3. **定时检查**:每30秒检查一次任务状态
4. **自动通知**:cron 定时(每2分钟)检查任务完成状态,任务完成后主动通知用户
5. **自动保存**:完成后自动保存 md 文件到 /tmp/

## 结果文件

任务完成后,md 文件自动保存到:
```
~/.openclaw/workspace/skills/zeelin-deep-research/reports/zeelin_主题_时间戳.md
```

## Cron 定时器

- **间隔**:每1分钟
- **功能**:检查任务完成状态
- **通知**:任务完成后主动发送消息给用户

Related Skills

autoresearch-pro

3891
from openclaw/skills

Automatically improve OpenClaw skills, prompts, or articles through iterative mutation-testing loops. Inspired by Karpathy's autoresearch. Use when user says 'optimize [skill]', 'autoresearch [skill]', 'improve my skill', 'optimize this prompt', 'improve my prompt', 'polish this article', 'improve this article', or explicitly requests quality improvement for any text-based content. Supports three modes: skill (SKILL.md files), prompt (any prompt text), and article (any document).

Workflow & Productivity

X/Twitter Research Skill

3891
from openclaw/skills

Research trending topics, ideas, and conversations on X (Twitter) using twitterapi.io.

Data & Research

token-research

3891
from openclaw/skills

Comprehensive token research for EVM chains (Base, ETH, Arbitrum) and Solana. Use this skill when you want to research crypto tokens, deep-dive projects or monitor tokens.

Data & Research

local-researcher

3891
from openclaw/skills

完全本地的深度研究助手 Skill。使用 Ollama 或 LMStudio 本地 LLM 进行迭代式网络研究,生成带引用来源的 Markdown 报告。当用户需要进行隐私优先的研究、本地文档分析或生成结构化研究报告时触发。

DeepSeek Agent Skill

3891
from openclaw/skills

Integrates DeepSeek API with OpenClaw agents.

auto-researcher

3891
from openclaw/skills

自主研究助手 - 深度调研、交叉验证、生成引用报告

MONK-EYE 👁️ - Deep Intelligence & Human Experience Oracle

3891
from openclaw/skills

MONK-EYE is a specialized OpenClaw skill designed for deep infiltration and synthesis of forum-based human intelligence. While most search tools focus on surface-level web pages, MONK-EYE dives into the "tacit knowledge" buried in the world's most active and niche forums (R10, BlackHatWorld, Reddit, Habr, etc.).

project-deep-analyzer

3891
from openclaw/skills

深度分析项目的系统边界、核心概念、模块架构、关键算法、技术选型以及错误排查。当用户需要深入理解代码库或定位疑难问题时调用。

Amazon Listing Optimizer — Free Listing Analysis & Keyword Research

3891
from openclaw/skills

**Free alternative to Helium 10 ($97/mo) and Jungle Scout ($49/mo).**

x-research

3891
from openclaw/skills

General-purpose X/Twitter research agent. Searches X for real-time perspectives, dev discussions, product feedback, cultural takes, breaking news, and expert opinions. Works like a web research agent but uses X as the source. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "/x-research", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic. NOT for: posting tweets, account management, or historical archive searches beyond 7 days.

deepwiki-ask

3891
from openclaw/skills

通过 DeepWiki MCP 查询仓库信息。支持提问、获取结构、获取文档内容。Query a repository via DeepWiki MCP: ask questions, get structure, get documentation. 用户提供 owner/repo 时触发。

competitive-research

3891
from openclaw/skills

Use when the user asks to research a competitor, map a market, analyze a category, or produce a competitive brief. Trigger phrases: 'research competitors of X', 'who competes with Y', 'market analysis for Z', 'competitive intelligence on [brand/space]', 'analyze this market', 'who are the main players in [category]', 'build a brief before my call', 'I need to understand this space'. Also triggers when preparing a proposal, positioning exercise, content strategy, or client pitch that requires knowing the competitive landscape.