| name | Paper AI Search |
| description | Use when the user describes a research need in natural language and wants AI-assisted query expansion before searching for papers, including requests to find recent work on a topic, related papers in a direction, or similar Chinese requests for AI paper search. |
| allowed-tools | ["searchArticles","readPaper"] |
Paper AI Search
Use this skill when the user gives a research question, a direction, or a vague paper-finding intent rather than a ready-made keyword list. The core workflow is query expansion first, then cross-source retrieval.
Workflow
- Rewrite the user's natural-language request into a cleaner academic search intent.
- Extract
3-6 compact keywords, each usually 1-3 words, favoring terms that would plausibly appear in titles or abstracts.
- Produce one refined semantic query sentence that captures the intent at a higher level.
- Search across all relevant academic sources with the expanded keywords rather than staying on a single source.
- Show the expanded keywords back to the user so the search process is inspectable and easy to refine.
Query Expansion Rules
- Cover the central technical concepts rather than relying on generic words.
- Mix narrower technical terms with slightly broader related terms to balance precision and recall.
- Avoid low-information tokens such as
method, model, or improvement unless they are part of a recognized phrase.
- If the request is underspecified, infer and separate the task, method family, and application setting.
Retrieval Sources
Search these sources by default:
arxivhuggingfacesemantic-scholarbiorxivpubmedpubchem
Output Structure
- Briefly restate the actual search intent.
- List the
Expanded keywords explicitly.
- Include a
Semantic query line when it adds clarity.
- Present the ranked paper shortlist. Each entry should include:
- original English title
- authors
- date
- source
- one sentence on why it matches the user's intent
- End with
Next step guidance:
- narrow the scope
- branch into a promising subtopic
- or move straight to summary / deep reading
Quality Rules
- Do not present query expansion as ground truth. It is only a retrieval strategy.
- Do not pad the answer with papers that are visibly unrelated to the expanded query.
- If the results are diffuse, state that the user request is still too broad.
- Preserve technical terms in their standard English form when that improves precision.
