Convert a baseline and problem frame into literature-grounded research directions.
npx skills add https://github.com/ResearAI/DeepScientist --skill idea-researai
Please help me install this Agent Skill. Skill: idea Source: https://github.com/ResearAI/DeepScientist/tree/main/src/skills/idea Command: npx skills add https://github.com/ResearAI/DeepScientist --skill idea-researai
Converts a given baseline and problem frame into executable, literature-grounded research directions that can be pursued as bounded experiments.
Generate a bounded slate of 6-12 raw ideas and converge to 2-3 serious candidates with clear justification.
High-intent search queries and answers about installing and using this skill.
To convert a baseline into testable research directions, the system analyzes your problem frame and literature survey to generate a limitations analysis, a bounded slate of 2-3 candidate frontiers, and a minimal validation plan.
Generating literature-grounded hypotheses requires synthesizing a literature survey with your baseline memory to produce 6-12 raw ideas, converging into 2-3 serious candidates with explicit rationale, evidence expectations, and rejection notes.
Narrowing raw ideation outputs into a bounded candidate frontier involves filtering 6-12 initial ideas down to 2-3 serious directions using literature survey evidence, limitations analysis, and structured reasoning to justify selections and rejections.
No, a completed literature survey and baseline memory are required inputs. The system needs both to perform limitations analysis and produce executable, literature-grounded research directions with a concrete minimal validation plan.
Yes, the ideation process provides a minimal validation plan. It generates a durable handoff artifact containing the selected idea, deferred ideas, rejection rationale, and a concrete validation plan ready for experimental planning.
A limitations analysis is produced by evaluating the baseline against the literature survey. If your output lacks this, ensure you provided a complete problem frame and baseline memory to generate the rejection rationale and evidence expectations.
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