web-research
Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Best use case
web-research is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Teams using web-research should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/web-research/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How web-research Compares
| Feature / Agent | web-research | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use this skill for requests related to web research; it provides a structured approach to conducting comprehensive web research
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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: 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`. ## 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
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