Decompose research topics into sub-problems and aggregate papers into structured tables.
npx skills add https://github.com/dogekiki/SP-test --skill gemini-search-dogekiki
Please help me install this Agent Skill. Skill: gemini-search Source: https://github.com/dogekiki/SP-test/tree/main/.trae/skills/gemini-search Command: npx skills add https://github.com/dogekiki/SP-test --skill gemini-search-dogekiki
This skill solves the problem of shallow literature discovery by using AI to decompose research topics into sub-problems, explore naming variants, and surface relevant papers that traditional keyword-based search engines often miss.
Use the gemini-search skill to find recent research papers on the topic of large language model quantization.
High-intent search queries and answers about installing and using this skill.
To find academic papers beyond simple keyword matching, use AI-driven literature discovery to decompose research topics into sub-problems and naming variants, surfacing relevant work that traditional search engines miss.
The best way to discover research papers on complex topics like transformer efficiency is decomposing the query into related sub-problems like pruning and quantization, aggregating papers from top venues, preprints, and repositories.
You format literature search results into structured tables by normalizing aggregated academic findings into structured formats, automatically extracting and organizing authors, venues, arXiv IDs, and code links.
Yes, you need the gemini-cli and gemini-mcp-tool installed to perform AI-powered literature discovery, as these dependencies execute multi-angle search queries and normalize academic results.
Yes, you can aggregate preprints and open-source repositories in a comprehensive literature search, because the multi-angle search queries specifically target top venues, preprints, and code repositories.
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