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deep-research-pro-litiao深入研究 Pro Litiao

Agent Skill

deep-research-pro-litiao 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

8,617

周安装

352

GitHub Stars

公开资料未说明

下载量

2,760
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:deep-research-pro-litiao(深入研究 Pro Litiao)
来源仓库:https://github.com/litiao1224/deep-research-pro-litiao
安装命令:
openclaw skills install deep-research-pro-litiao
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 deep-research-pro-litiao

简介

多源深度研究代理。搜索网络、综合调查结果并提供引用的报告。使用 Tavily API(首选)或 DuckDuckGo(后备)。

SKILL.md

name
deep-research-pro-litiao
version
1.1.0
description
Multi-source deep research agent. Searches the web, synthesizes findings, and delivers cited reports. Uses Tavily API (preferred) or DuckDuckGo (fallback).
homepage
https://github.com/paragshah/deep-research-pro
metadata
{"clawdbot":{"emoji":"🔬","category":"research","requires":{"env":["TAVILY_API_KEY"]}}}

Deep Research Pro 🔬

A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. Prefers Tavily API for cleaner, AI-optimized results — falls back to DuckDuckGo if API key unavailable.

How It Works

When the user asks for research on any topic, follow this workflow:

Step 1: Understand the Goal (30 seconds)

Ask 1-2 quick clarifying questions:

  • "What's your goal — learning, making a decision, or writing something?"
  • "Any specific angle or depth you want?"

If the user says "just research it" — skip ahead with reasonable defaults.

Step 2: Plan the Research (think before searching)

Break the topic into 3-5 research sub-questions. For example:

  • Topic: "Impact of AI on healthcare"

- What are the main AI applications in healthcare today? - What clinical outcomes have been measured? - What are the regulatory challenges? - What companies are leading this space? - What's the market size and growth trajectory?

Step 3: Execute Multi-Source Search

Preferred: Use Tavily Search (if TAVILY_API_KEY is available):

# General web search
cd ~/.openclaw/workspace/skills/tavily-search-litiao
node scripts/search.mjs "<sub-question keywords>" -n 10

# News search (for current events)
node scripts/search.mjs "<topic>" --topic news --days 3

# Deep search (for complex topics)
node scripts/search.mjs "<complex query>" --deep

Fallback: DuckDuckGo (if Tavily unavailable):

# Web search
/home/clawdbot/clawd/skills/ddg-search/scripts/ddg "<sub-question keywords>" --max 8

# News search (for current events)
/home/clawdbot/clawd/skills/ddg-search/scripts/ddg news "<topic>" --max 5

Search strategy:

  • Use 2-3 different keyword variations per sub-question
  • Mix web + news searches
  • Aim for 15-30 unique sources total
  • Prioritize: academic, official, reputable news > blogs > forums
  • Tavily advantage: Returns cleaner snippets, better for AI synthesis

Step 4: Deep-Read Key Sources

For the most promising URLs, fetch full content:

curl -sL "<url>" | python3 -c "
import sys, re
html = sys.stdin.read()
# Strip tags, get text
text = re.sub('<[^>]+>', ' ', html)
text = re.sub(r'\s+', ' ', text).strip()
print(text[:5000])
"

Read 3-5 key sources in full for depth. Don't just rely on search snippets.

Step 5: Synthesize & Write Report

Structure the report as:

# [Topic]: Deep Research Report
*Generated: [date] | Sources: [N] | Confidence: [High/Medium/Low]*

## Executive Summary
[3-5 sentence overview of key findings]

## 1. [First Major Theme]
[Findings with inline citations]
- Key point ([Source Name](url))
- Supporting data ([Source Name](url))

## 2. [Second Major Theme]
...

## 3. [Third Major Theme]
...

## Key Takeaways
- [Actionable insight 1]
- [Actionable insight 2]
- [Actionable insight 3]

## Sources
1. [Title](url) — [one-line summary]
2. ...

## Methodology
Searched [N] queries across web and news. Analyzed [M] sources.
Sub-questions investigated: [list]

Step 6: Save & Deliver

Save the full report:

mkdir -p ~/clawd/research/[slug]
# Write report to ~/clawd/research/[slug]/report.md

Then deliver:

  • Short topics: Post the full report in chat
  • Long reports: Post the executive summary + key takeaways, offer full report as file

Quality Rules

  1. Every claim needs a source. No unsourced assertions.
  2. Cross-reference. If only one source says it, flag it as unverified.
  3. Recency matters. Prefer sources from the last 12 months.
  4. Acknowledge gaps. If you couldn't find good info on a sub-question, say so.
  5. No hallucination. If you don't know, say "insufficient data found."

Examples

"Research the current state of nuclear fusion energy"
"Deep dive into Rust vs Go for backend services in 2026"
"Research the best strategies for bootstrapping a SaaS business"
"What's happening with the US housing market right now?"

For Sub-Agent Usage

When spawning as a sub-agent, include the full research request and context:

sessions_spawn(
  task: "Run deep research on [TOPIC]. Follow the deep-research-pro SKILL.md workflow.
  Read /home/clawdbot/clawd/skills/deep-research-pro/SKILL.md first.
  Goal: [user's goal]
  Specific angles: [any specifics]
  Save report to ~/clawd/research/[slug]/report.md
  When done, wake the main session with key findings.",
  label: "research-[slug]",
  model: "opus"
)

Requirements

Preferred:

  • Tavily API key: TAVILY_API_KEY (get from https://tavily.com)
  • Tavily scripts: ~/.openclaw/workspace/skills/tavily-search-litiao/scripts/

Fallback (no API key needed):

  • DDG search script: /home/clawdbot/clawd/skills/ddg-search/scripts/ddg

Both methods:

  • curl (for fetching full pages)

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

76.99%
按下载量换算2,125

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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 warning/failed 结果,不能写成本站确认安全。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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