Web Research
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.
- Skill ID
- langchain-ai/deepagents/web-research
- Publisher
- langchain-ai
- Repository
- deepagents
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
langchain-ai/deepagents/web-researchInstalls these files- SKILL.md
What this skill tells the agent
Web Research Skill
Research Process
Step 1: Create and Save Research Plan
Before delegating to subagents, you MUST:
- 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.
- Analyze the research question - Break it down into distinct, non-overlapping subtopics
- Write a research plan file - Use the
write_filetool to createresearch_[topic_name]/research_plan.mdcontaining:
- 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:
- 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
- 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:
- Review the findings files that were saved locally:
- First run
list_files research_[topic_name]to see what files were created - Then use
read_filewith the file paths (e.g.,research_[topic_name]/findings_*.md) - Important: Use
read_filefor LOCAL files only, not URLs
- 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
- Write final report (optional) - Use
write_fileto createresearch_[topic_name]/research_report.mdif 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
More from langchain-ai
Use this skill in a project
Open any RiverX project, search the Skills panel for langchain-ai/deepagents/web-research, and install it in one click.
