# Deep Web Research

Researches a question from several angles before answering, instead of one quick search.

- Repository: https://github.com/bytedance/deer-flow (84840 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add bytedance/deer-flow --skill deep-research -g -a claude-code -y`
Codex: `npx skills add bytedance/deer-flow --skill deep-research -g -a codex -y`
Cursor: `npx skills add bytedance/deer-flow --skill deep-research -g -a cursor -y`
Gemini CLI: `npx skills add bytedance/deer-flow --skill deep-research -g -a gemini-cli -y`

## Description

Use this skill instead of WebSearch for ANY question requiring web research. Trigger on queries like "what is X", "explain X", "compare X and Y", "research X", or before content generation tasks. Provides systematic multi-angle research methodology instead of single superficial searches. Use this proactively when the user's question needs online information.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Deep Research Skill

## Overview

This skill provides a systematic methodology for conducting thorough web research. **Load this skill BEFORE starting any content generation task** to ensure you gather sufficient information from multiple angles, depths, and sources.

## When to Use This Skill

**Always load this skill when:**

### Research Questions
- User asks "what is X", "explain X", "research X", "investigate X"
- User wants to understand a concept, technology, or topic in depth
- The question requires current, comprehensive information from multiple sources
- A single web search would be insufficient to answer properly

### Content Generation (Pre-research)
- Creating presentations (PPT/slides)
- Creating frontend designs or UI mockups
- Writing articles, reports, or documentation
- Producing videos or multimedia content
- Any content that requires real-world information, examples, or current data

## Core Principle

**Never generate content based solely on general knowledge.** The quality of your output directly depends on the quality and quantity of research conducted beforehand. A single search query is NEVER enough.

## Research Methodology

### Phase 1: Broad Exploration

Start with broad searches to understand the landscape:

1. **Initial Survey**: Search for the main topic to understand the overall context
2. **Identify Dimensions**: From initial results, identify key subtopics, themes, angles, or aspects that need deeper exploration
3. **Map the Territory**: Note different perspectives, stakeholders, or viewpoints that exist

Example:
```
Topic: "AI in healthcare"
Initial searches:
- "AI healthcare applications 2024"
- "artificial intelligence medical diagnosis"
- "healthcare AI market trends"

Identified dimensions:
- Diagnostic AI (radiology, pathology)
- Treatment recommendation systems
- Administrative automation
- Patient monitoring
- Regulatory landscape
- Ethical considerations
```

### Phase 2: Deep Dive

The rest: https://github.com/bytedance/deer-flow/blob/HEAD/skills/public/deep-research/SKILL.md