get_field_orientation
Retrieves and ranks foundational papers for a research topic by citation impact and relevance. Bootstraps literature surveys with candidate papers for fast field orientation.
Instructions
Returns CANDIDATE FOUNDATIONAL PAPERS for a research topic — cheap retrieval only, no synthesis. Ranks papers by a blend of citation count (0.6 weight, captures importance) and semantic similarity to your topic (0.4 weight). Use this to bootstrap a literature survey or get a fast sense of the landscape. For a synthesized orientation report (key concepts, open problems, reading order), use the /field-guide skill which calls this tool internally. Does not require a Pro API key — no LLM calls are made.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Research area to orient on. Be specific for better results. Examples: 'diffusion models for protein structure prediction', 'efficient attention mechanisms for long-context LLMs', 'graph neural networks for molecular property prediction'. | |
| limit | No | Number of candidate papers to return (5–30, default 15). |