Orchestrate search, fetch, and model generation to produce structured research reports.
npx skills add https://github.com/Yaron9/MetaMe --skill deep-research-yaron9
Please help me install this Agent Skill. Skill: deep-research Source: https://github.com/Yaron9/MetaMe/tree/main/skills/deep-research Command: npx skills add https://github.com/Yaron9/MetaMe --skill deep-research-yaron9
This multi-step research assistant orchestrates broad-to-deep exploration by combining WebSearch, WebFetch, and LLM generation to deliver structured insights across any topic.
Provide a topic and the skill will perform an iterative deep-dive research cycle and produce a structured report.
High-intent search queries and answers about installing and using this skill.
To generate a structured research report, you provide a topic and the assistant performs iterative multi-angle web searches, fetches high-quality pages, and synthesizes findings into sections like background, principles, and future outlook.
Iterative deep-dive research is a multi-step exploration process that repeatedly searches and fetches web data from multiple angles. You need it when a single search is insufficient and your topic requires synthesizing sources into a comprehensive report.
Yes, you can supply optional NotebookLM-based private knowledge sources. The assistant integrates these private sources with public web search and fetch results to enhance the final structured report generation.
You extract key findings by using WebFetch to retrieve high-quality page content after WebSearch identifies relevant sources. The process tracks new questions and issues during extraction to refine subsequent iterative searches.
Yes, deep research works for comparisons by executing 3-5 iterative query angles. It explicitly explores definitions, technical principles, latest developments, applications, and competitors to ensure comprehensive multi-angle coverage.
The limitations of automated search and fetch include relying on public web page accessibility and quality. While private sources like NotebookLM can supplement results, the final structured report depends on the accuracy of extracted findings.
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