
web-research
by langchain-ai
Deep Agents is an agent harness built on langchain and langgraph. Deep Agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped to handle complex agentic tasks.
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SKILL.md
name: web-research description: Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Web Research Skill
This skill provides a structured approach to conducting comprehensive web research using the task tool to spawn research subagents. It emphasizes planning, efficient delegation, and systematic synthesis of findings.
When to Use This Skill
Use this skill when you need to:
- Research complex topics requiring multiple information sources
- Gather and synthesize current information from the web
- Conduct comparative analysis across multiple subjects
- Produce well-sourced research reports with clear citations
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
tasktool 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
- First run
-
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.
Available Tools
You have access to:
- write_file: Save research plans and findings to local files
- read_file: Read local files (e.g., findings saved by subagents)
- list_files: See what local files exist in a directory
- fetch_url: Fetch content from URLs and convert to markdown (use this for web pages, not read_file)
- task: Spawn research subagents with web_search access
Research Subagent Configuration
Each subagent you spawn will have access to:
- web_search: Search the web using Tavily (parameters: query, max_results, topic, include_raw_content)
- write_file: Save their findings to the filesystem
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
Score
Total Score
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