Skip to content
Agentmart
Submit a tool

web-research

Searches multiple web sources, synthesizes findings, and produces cited research reports using delegated subagents.

Skill by langchain-aiOfficial

IndexedMIT★ 30,550
Write a review

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.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

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.

Use cases: documents, research, deep-research

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
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.

More from langchain-ai/deepagents

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
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from langchain-ai

Cite this page

web-research skill. Agent Mart. https://agentmart.dev/skills/langchain-ai-web-research (last updated 2026-10-24)