skills/68-research-productivity-skills/web-research/SKILL.md
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.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research web-researchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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_file tool to create research_[topic_name]/research_plan.md containing:
Planning Guidelines:
For each subtopic in your plan:
Use the task tool to spawn a research subagent with:
research_[topic_name]/findings_[subtopic].mdRun 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.
After all subagents complete:
Review the findings files that were saved locally:
list_files research_[topic_name] to see what files were createdread_file with the file paths (e.g., research_[topic_name]/findings_*.md)read_file for LOCAL files only, not URLsSynthesize the information - Create a comprehensive response that:
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.
tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.