web-research
Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents.
Skill by langchain-aiOfficial
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/langchain-ai-web-research
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, research, deep-research
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
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- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/web-research
What's inside
- Skill name
web-research- Description
- Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents. Use when the user asks to research a topic online, search the web, look something up, find current information, compare options, or produce a research report.
- License
- MIT
- Instructions
- 74 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Web Research Skill ## Research Process ### Step 1: Create and Save Research Plan Before delegating to subagents, you MUST: 1. **Create a research folder** - Organize all research files in a dedicated folder relative to the current working directory: ``` mkdir research_[topic_name] ``` This keeps files organized and prevents clutter in the working directory. 2. **Analyze the research question** - Break it down into distinct, non-overlapping subtopics 3. **Write a research plan file** - Use the `write_file` tool to create `research_[topic_name]/research_plan.md` containing: - The main research question - 2-5 specific subtopics to investigate - Expected information from each subtopic - How results will be synthesized **Planning Guidelines:** - **Simple fact-finding**: 1-2 subtopics - **Comparative analysis**: 1 subtopic per comparison element (max 3) - **Complex investigations**: 3-5 subtopics ### Step 2: Delegate to Research Subagents For each subtopic in your plan: 1. **Use the `task` tool** to spawn a research subagent with: - Clear, specific research question (no acronyms) - Instructions to write findings to a file: `research_[topic_name]/findings_[subtopic].md` - Budget: 3-5 web searches maximum 2. **Run up to 3 subagents in parallel** for efficient research **Subagent Instructions Template:** ``` Research [SPECIFIC TOPIC]. Use the web_search tool to gather information. After completing your research, use write_file to save your findings to research_[topic_name]/findings_[subtopic].md. Include key facts, relevant quotes, and source URLs. Use 3-5 web searches maximum. ``` ### Step 3: Synthesize Findings After all subagents complete: 1. **Review the findings files** that were saved locally: - First run `list_files research_[topic_name]` to see what files were created - Then use `read_file` with the **file paths** (e.g., `research_[topic_name]/findings_*.md`) - **Important**: Use `read_file` for LOCAL files only, not URLs 2. **Synthesize the information** - Create a comprehensive response that: - Directly answers the original question - Integrates insights from all subtopics - Cites specific sources with URLs (from the findings files) - Identifies any gaps or limitations 3. **Write final report** (optional) - Use `write_file` to create `research_[topic_name]/research_report.md` if requested **Note**: If you need to fetch additional information from URLs, use the `fetch_url` tool, not `read_file`. ## Best Practices - **Plan before delegating** - Always write research_plan.md first - **Clear subtopics** - Ensure each subagent has distinct, non-overlapping scope - **File-based communication** - Have subagents save findings to files, not return them directly - **Systematic synthesis** - Read all findings files before creating final response - **Stop appropriately** - Don't over-research; 3-5 searches per subtopic is usually sufficient
From langchain-ai/deepagents, MIT.
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Compare and alternatives
Featured in
Signals
- Stars
- 30,550
- Forks
- 4,302
- Open issues
- 163
- Last commit (this folder)
- May 12, 2026 (5 months ago)
- Last release
- Oct 23, 2026 (3 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/langchain-ai/deepagents
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
web-research skill. Agent Mart. https://agentmart.dev/skills/langchain-ai-web-research (last updated 2026-10-24)