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idea-discovery

Automate research idea discovery with literature survey and pilot experiments.

2|Updated Aug 12, 2025
Search Tags:#idea validation#academic research#research pipeline#literature survey#pilot experiment#novelty verification#research idea discovery
One-click install
npx skills add https://github.com/goupup-ai/miccai25 --skill idea-discovery-goupup-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: idea-discovery
Source: https://github.com/goupup-ai/miccai25/tree/main/ARIS/skills/idea-discovery
Command: npx skills add https://github.com/goupup-ai/miccai25 --skill idea-discovery-goupup-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Researchers and R&D teams often waste weeks manually sifting through literature, brainstorming ideas, and validating feasibility only to find most concepts are unoriginal or unworkable. This skill automates the full end-to-end idea discovery pipeline to cut this process down to hours, delivering only validated, high-potential research ideas.

Core Features & Use Cases

  • End-to-end automated pipeline: Chains literature survey, idea brainstorming, novelty verification, critical peer review, pilot experiment execution, and method refinement into a single seamless workflow.
  • Empirical validation first: Runs parallel pilot experiments on available GPUs to test idea feasibility, prioritizing concepts with positive real-world signal over unproven theoretical ideas.
  • Use case: A researcher working on medical image segmentation can input their broad research direction, and the skill will output a ranked list of validated ideas with full experiment plans, eliminating unoriginal or unfeasible concepts early.

Quick Start

Use the idea-discovery skill with your research direction, such as "efficient vertebrae segmentation for blurred medical images", to run the full end-to-end pipeline and get ranked, validated research ideas with experiment plans.

Frequently Asked Questions about idea-discovery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate the research idea discovery pipeline for academic literature?▼

Research idea discovery automation uses a pipeline that chains literature survey, novelty verification, and pilot experiments to generate validated research proposals. This skill coordinates those sub-skills to reduce manual effort and accelerate concept generation.

What is the best way to validate research ideas with empirical evidence before submission?▼

Validating research ideas with empirical evidence requires running parallel pilot experiments on available GPUs to test feasibility. This skill prioritizes concepts with positive real-world signal over unproven theoretical ideas, delivering ranked, submission-ready research proposals.

Can I use this automated idea validation for medical imaging and computer vision research?▼

Yes, automated idea validation targets academic researchers and AI R&D teams in domains including medical imaging, computer vision, and machine learning. You input a broad research direction like efficient vertebrae segmentation and receive validated, pilot-tested ideas.

How do I run a literature survey and novelty verification for machine learning concepts?▼

Running a literature survey and novelty verification for machine learning concepts is handled by chaining these sub-skills within an automated end-to-end pipeline. It eliminates unoriginal or unfeasible concepts early by cross-checking against existing literature.

Do I need available GPUs to execute the pilot experiment execution step?▼

Yes, available GPUs are required for pilot experiment execution. The pipeline runs parallel pilot experiments on available GPUs to test idea feasibility and prioritize concepts with positive real-world signal over unproven theoretical ideas.

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