light-idea-generation

Generate and evaluate research ideas with structured ideation outputs.

514|67|Updated Jun 7, 2026

Search Tags:#feasibility #knowledge-management #ranking #literature-review #openalex #research-design #idea-generation

Ready to run

npx skills add https://github.com/Light0305/Light-skills --skill light-idea-generation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: light-idea-generation
Source: https://github.com/Light0305/Light-skills/tree/main/skills/light-idea-generation
Command: npx skills add https://github.com/Light0305/Light-skills --skill light-idea-generation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps researchers rapidly generate high-potential, differentiated research ideas tailored to their project context, data, and constraints, and records them in a structured format for rapid review.

Core Features & Use Cases

Structured ideation: integrates project background, data feasibility, tech stack, and timeline to propose ideas with clear novelty, impact, and feasibility.
Level-agnostic justification: supports Level 1 (clear direction) and Level 2 (direction from data or literature) ideation, with traceable evidence and a plan for validation.
Governance-ready outputs: produces idea_candidates.md ready for m04 critique, with detailed justification, most-similar prior work, and data/compute estimates.

Quick Start

输入项目背景、数据条件与目标，AI 将输出可直接送审的立项卡草案与分层候选想法。

Frequently Asked Questions about light-idea-generation

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

FAQPage Schema

How do I generate structured research ideas with literature-backed novelty checks?▼

Generate structured research ideas by inputting project context and data to trigger level-aware ideation workflows, applying literature-backed novelty assessment, feasibility checks, and an evaluation rubric to output a ranked shortlist with supporting evidence.

What is the best way to evaluate research feasibility and impact before project design?▼

Evaluating research feasibility and impact requires applying a rigorous evaluation rubric to your project context and data, producing a ranked shortlist of idea candidates with detailed justification, most-similar prior work, and data or compute estimates.

How do I prepare project context and data for level-aware research idea generation?▼

Prepare project context and data for research idea generation by defining your Level 1 clear direction or Level 2 data-driven direction, ensuring you outline background, data availability, tech stack, and timeline to generate actionable plans.

Can I use OpenAlex literature reviews to assess novelty during research design?▼

Yes, you can use OpenAlex for literature reviews to support novelty assessment during research design, integrating the findings with data feasibility and project constraints to produce structured ideation outputs.

Does this research idea generation method support both data-driven and direction-based ideation?▼

Yes, this method supports both Level 1 clear direction and Level 2 data-driven or literature-driven ideation, applying level-agnostic justification and traceable evidence to generate governance-ready idea candidates.

What are the limitations of automated research idea generation for project design?▼

Automated research idea generation outputs a ranked shortlist and supporting evidence formatted for critique, but it requires defined project context and data constraints, meaning it cannot replace independent validation during final project design.