Web Research
Juncai22/spring-ai-agent-learning
A skill your agent uses for requests related to web research; it provides a structured approach to conducting comprehensive web research
Replaces single quick searches with a staged research routine of broad survey, targeted deep dives and cross-checking, run before the agent writes anything that needs facts.
Install Deep Web Research Method
$ npx skills add bytedance/deer-flow --skill deep-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install bytedance/deer-flow deep-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/public/deep-research .claude/skills/deep-research && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "deep-research" agent skill from https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-research into .claude/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-researchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add bytedance/deer-flow --skill deep-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install bytedance/deer-flow deep-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/public/deep-research .agents/skills/deep-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deep-research" agent skill from https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-research into .agents/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add bytedance/deer-flow --skill deep-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install bytedance/deer-flow deep-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/public/deep-research .cursor/skills/deep-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "deep-research" agent skill from https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-research into .cursor/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/bytedance/deer-flow.git --path skills/public/deep-research--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add bytedance/deer-flow --skill deep-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install bytedance/deer-flow deep-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/public/deep-research .gemini/skills/deep-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "deep-research" agent skill from https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-research into .gemini/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install bytedance/deer-flow deep-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add bytedance/deer-flow --skill deep-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/public/deep-research .github/skills/deep-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "deep-research" agent skill from https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-research into .github/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add bytedance/deer-flow --skill deep-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install bytedance/deer-flow deep-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bytedance/deer-flow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/public/deep-research .opencode/skills/deep-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "deep-research" agent skill from https://github.com/bytedance/deer-flow/tree/main/skills/public/deep-research into .opencode/skills/deep-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deep-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
deep-research- GitHub stars
- 83k
- Used in
- 5 other repos
- Token cost
- ~2k tokens
- SKILL.md length
- 817 words
- Files
- 1
- Skills in repo
- 23
- Repo updated
- First seen
- Licence
- MIT
At a glance
Replaces single quick searches with a staged research routine of broad survey, targeted deep dives and cross-checking, run before the agent writes anything that needs facts.
- Works in 4 steps: Broad Exploration → Deep Dive → Diversity & Validation → …
- Researching an unfamiliar technology before comparing it with alternatives
- SKILL.md covers Overview, When to Use This Skill, Core Principle and Research Methodology, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
This skill sets one rule: the agent should not produce content from general knowledge alone, and one search query is never enough. Research runs in phases. The first is a broad survey of the topic to find its subtopics, themes and competing viewpoints. The second is a deep dive on each dimension, using precise keywords, several phrasings of the same query, full-page reads through `web_fetch` instead of snippets, and following references that sources point to.
A third phase looks for different kinds of information so the picture does not rest on one type of source; the table that lists them is cut off in the excerpt. The skill is meant to be loaded ahead of content work such as presentations, interface mockups, articles, reports and videos, and for questions like explaining or comparing technologies. It depends on web search and fetch tools being available to the agent.
When your agent uses it
- Researching an unfamiliar technology before comparing it with alternatives
- Gathering current facts and examples before drafting a report or article
- Preparing background for a presentation that needs real data rather than general knowledge
Example prompts
- “Research how hospitals are using AI for radiology and summarize the main approaches.”
- “Compare Kafka and Pulsar for event streaming, checking several sources.”
- “Before you write the slides, investigate what is known about heat pump adoption in Europe.”
Requirements
- Web search and a `web_fetch` tool available to the agent
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit be34cc4. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Deep Web Research Method loads about 2k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 817 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from bytedance/deer-flow at commit be34cc4, republished under its MIT licence (© bytedance). 817 words, ~1,962 tokens.
Download SKILL.mdSave it as
.claude/skills/deep-research/SKILL.md (or your agent's skills folder).- name
- deep-research
- 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.
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:
- Initial Survey: Search for the main topic to understand the overall context
- Identify Dimensions: From initial results, identify key subtopics, themes, angles, or aspects that need deeper exploration
- 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 considerationsPhase 2: Deep Dive
For each important dimension identified, conduct targeted research:
- Specific Queries: Search with precise keywords for each subtopic
- Multiple Phrasings: Try different keyword combinations and phrasings
- Fetch Full Content: Use
web_fetchto read important sources in full, not just snippets - Follow References: When sources mention other important resources, search for those too
Example:
Dimension: "Diagnostic AI in radiology"
Targeted searches:
- "AI radiology FDA approved systems"
- "chest X-ray AI detection accuracy"
- "radiology AI clinical trials results"
Then fetch and read:
- Key research papers or summaries
- Industry reports
- Real-world case studiesPhase 3: Diversity & Validation
Ensure comprehensive coverage by seeking diverse information types:
| Information Type | Purpose | Example Searches |
|---|---|---|
| Facts & Data | Concrete evidence | "statistics", "data", "numbers", "market size" |
| Examples & Cases | Real-world applications | "case study", "example", "implementation" |
| Expert Opinions | Authority perspectives | "expert analysis", "interview", "commentary" |
| Trends & Predictions | Future direction | "trends 2024", "forecast", "future of" |
| Comparisons | Context and alternatives | "vs", "comparison", "alternatives" |
| Challenges & Criticisms | Balanced view | "challenges", "limitations", "criticism" |
Phase 4: Synthesis Check
Before proceeding to content generation, verify:
- Have I searched from at least 3-5 different angles?
- Have I fetched and read the most important sources in full?
- Do I have concrete data, examples, and expert perspectives?
- Have I explored both positive aspects and challenges/limitations?
- Is my information current and from authoritative sources?
If any answer is NO, continue researching before generating content.
Search Strategy Tips
Effective Query Patterns
# Be specific with context
❌ "AI trends"
✅ "enterprise AI adoption trends 2024"
# Include authoritative source hints
"[topic] research paper"
"[topic] McKinsey report"
"[topic] industry analysis"
# Search for specific content types
"[topic] case study"
"[topic] statistics"
"[topic] expert interview"
# Use temporal qualifiers — always use the ACTUAL current year from <current_date>
"[topic] 2026" # ← replace with real current year, never hardcode a past year
"[topic] latest"
"[topic] recent developments"Show full SKILL.md (410 more words)Show less
Temporal Awareness
Always check <current_date> in your context before forming ANY search query.
<current_date> gives you the full date: year, month, day, and weekday (e.g. 2026-02-28, Saturday). Use the right level of precision depending on what the user is asking:
| User intent | Temporal precision needed | Example query |
|---|---|---|
| "today / this morning / just released" | Month + Day | "tech news February 28 2026" |
| "this week" | Week range | "technology releases week of Feb 24 2026" |
| "recently / latest / new" | Month | "AI breakthroughs February 2026" |
| "this year / trends" | Year | "software trends 2026" |
Rules:
- When the user asks about "today" or "just released", use month + day + year in your search queries to get same-day results
- Never drop to year-only when day-level precision is needed —
"tech news 2026"will NOT surface today's news - Try multiple phrasings: numeric form (
2026-02-28), written form (February 28 2026), and relative terms (today,this week) across different queries
❌ User asks "what's new in tech today" → searching "new technology 2026" → misses today's news
✅ User asks "what's new in tech today" → searching "new technology February 28 2026" + "tech news today Feb 28" → gets today's results
When to Use web_fetch
Use web_fetch to read full content when:
- A search result looks highly relevant and authoritative
- You need detailed information beyond the snippet
- The source contains data, case studies, or expert analysis
- You want to understand the full context of a finding
Iterative Refinement
Research is iterative. After initial searches:
- Review what you've learned
- Identify gaps in your understanding
- Formulate new, more targeted queries
- Repeat until you have comprehensive coverage
Quality Bar
Your research is sufficient when you can confidently answer:
- What are the key facts and data points?
- What are 2-3 concrete real-world examples?
- What do experts say about this topic?
- What are the current trends and future directions?
- What are the challenges or limitations?
- What makes this topic relevant or important now?
Common Mistakes to Avoid
- ❌ Stopping after 1-2 searches
- ❌ Relying on search snippets without reading full sources
- ❌ Searching only one aspect of a multi-faceted topic
- ❌ Ignoring contradicting viewpoints or challenges
- ❌ Using outdated information when current data exists
- ❌ Starting content generation before research is complete
Output
After completing research, you should have:
- A comprehensive understanding of the topic from multiple angles
- Specific facts, data points, and statistics
- Real-world examples and case studies
- Expert perspectives and authoritative sources
- Current trends and relevant context
Only then proceed to content generation, using the gathered information to create high-quality, well-informed content.
© bytedance, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/public/deep-research of bytedance/deer-flow.
Open the folder on GitHubat commit be34cc4
Used in 5 other repositories
We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in bytedance/deer-flow, which our catalogue first saw on October 7, 2026.
- ljxpython/ai-agent-platformapps/runtime-service/src/runtime_service/services/dearflow_agent/skills/deep-research
- MagicCube/agentarauser-home/.claude/skills/deep-research
- stophobia/deerflow2.0-enhancedskills/public/deep-research
- BingHanOfUESTC/open_agent_teamteams/paper_survey_team/skills/deep-research
- majiayu000/claude-skill-registryskills/analysis/deep-research-bytedance-deer-flow
Compare with similar skills
Deep Web Research Method next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Deep Web Research Method this skillbytedance/deer-flow | 83k | 5 repos | ~2k | Automated safety check: Pass | MIT | |
| Web ResearchJuncai22/spring-ai-agent-learning | 123 | 3 repos | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Bmad Deep Recondelorenj/mcp-server-trello | 445 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Net Deep Researchh4444433333/net-deep-research | 123 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Ray Trend Searchimraywang/rayskills | 160 | — | ~2.1k | Automated safety check: Pass | Custom licence | |
| Argo Search and Verificationtaxueseek/argo | 185 | — | ~1.2k | Automated safety check: Pass | MIT |
Similar skills
Bmad Deep Recon
delorenj/mcp-server-trello
Decision-grade research, three ways: draft a deep-research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), process a finished research report — file it, distill…
Net Deep Research
h4444433333/net-deep-research
Runs cross-source web research to verify whether an online claim is true, distinguishing confirmed facts from rumor, marketing claims or stale information.
Ray Trend Search
imraywang/rayskills
Researches what people are saying about a topic over a recent window across X, Reddit, YouTube and the public web, reporting each source's status with links.
Argo Search and Verification
taxueseek/argo
Unified web search, page fetching and evidence checking across hundreds of sources, with result verification, a research-dossier mode and vertical search engines.
Exa Search
majiayu000/claude-skill-registry
Neural search via Exa MCP for web, code, and company research.
More from bytedance/deer-flow
All 23 skills in this repoVercel Deploy
bytedance/deer-flow
Deploys a project to Vercel with one script and no login, then returns a live preview URL and a claim link for moving the deployment into your own Vercel account.
Chart Visualization
bytedance/deer-flow
Picks a suitable chart type from 26 options for your data, maps the data to that chart's parameters and generates a chart image through a JavaScript script.
GitHub Deep Research
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
Structured Image Generation
bytedance/deer-flow
Turns an image request into a structured JSON prompt and runs a bundled Python script to generate the picture, optionally guided by reference images.
Excel and CSV Data Analysis
bytedance/deer-flow
Analyzes uploaded Excel and CSV files with SQL through DuckDB, producing schema inspections, statistical summaries and exports to CSV, JSON or Markdown.
DeerFlow Smoke Test
bytedance/deer-flow
Walks through an end-to-end smoke test of a DeerFlow deployment: pull the latest code, deploy with Docker or locally, verify services, run health checks and write a report.
Related
Categories
Questions about Deep Web Research Method
What does Deep Web Research Method do?
Replaces single quick searches with a staged research routine of broad survey, targeted deep dives and cross-checking, run before the agent writes anything that needs facts. This skill sets one rule: the agent should not produce content from general knowledge alone, and one search query is never enough. Research runs in phases.
When should I use Deep Web Research Method?
Deep Web Research Method fits situations like: researching an unfamiliar technology before comparing it with alternatives; gathering current facts and examples before drafting a report or article; preparing background for a presentation that needs real data rather than general knowledge.
How do I install Deep Web Research Method in Claude Code?
Run `npx skills add bytedance/deer-flow --skill deep-research -a claude-code`. Or copy the skill folder (skills/public/deep-research in bytedance/deer-flow) into .claude/skills/deep-research in your project. Claude Code loads it when a task matches its description.
How do I install Deep Web Research Method in Codex?
Run `npx skills add bytedance/deer-flow --skill deep-research -a codex`. Or copy the skill folder (skills/public/deep-research in bytedance/deer-flow) into .agents/skills/deep-research in your project. Codex loads it when a task matches its description.
Can I use Deep Web Research Method in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bytedance/deer-flow --skill deep-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deep-research, .gemini/skills/deep-research, .github/skills/deep-research and .opencode/skills/deep-research in your project.
What does Deep Web Research Method need to run?
SKILL.md names no scripts, command-line tools or credentials: Deep Web Research Method is instructions for the agent only. Our summary lists: Web search and a `web_fetch` tool available to the agent.
Does Deep Web Research Method access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Deep Web Research Method safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Deep Web Research Method use?
Deep Web Research Method is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Deep Web Research Method use?
About 2k tokens (SKILL.md is roughly 7.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Deep Web Research Method?
Skills that share tags, products or a category with Deep Web Research Method: Web Research (Juncai22/spring-ai-agent-learning, 123 stars), Bmad Deep Recon (delorenj/mcp-server-trello, 445 stars), Net Deep Research (h4444433333/net-deep-research, 123 stars) and Ray Trend Search (imraywang/rayskills, 160 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Deep Web Research Method?
bytedance (a GitHub organization) maintains it in bytedance/deer-flow, which has 83,484 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on October 8, 2026.
Source: bytedance/deer-flow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.