AMiner Deep Search

ReAct-style survey paper collection using OpenAI-compatible model calls and AMiner search/reference APIs.

Use this skill when the user asks to collect papers for a research topic, build a large literature list, run citation snowballing, or prepare survey references.

What This Skill Does

The framework runs an LLM-controlled loop with these tools:

• search: AMiner keyword search, returning up to 20 papers per query.
• get_reference: AMiner backward-reference expansion for selected seed papers.
• add_to_paper_set: deduplicated paper collection by AMiner paper ID.
• END: terminate and output [{"id": "...", "title": "..."}, ...].

The controller prompt asks the model to expand queries, prioritize high-quality seed papers, use reference snowballing, and terminate within 50 rounds. The target collection size is 400+ papers when AMiner results support it; it must not fabricate papers.

Required Environment Variables