_generate-ideas

Name: _generate-ideas
Availability: InStock
Author: inference-sim

Generate and iteratively refine research ideas with multi-model reviewer feedback.

2|1|Updated Feb 17, 2026

Search Tags:#research #problem solving #idea generation #iterative development #synthesis #ai review

Ready to run

npx skills add https://github.com/inference-sim/sdlc-plugins --skill generate-ideas

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: _generate-ideas
Source: https://github.com/inference-sim/sdlc-plugins/tree/main/plugins/research-ideas/skills/_generate-ideas
Command: npx skills add https://github.com/inference-sim/sdlc-plugins --skill generate-ideas

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the iterative generation and review of research ideas, ensuring each new idea builds upon previous feedback and addresses all problem constraints.

Core Features & Use Cases

Iterative Idea Generation: Creates multiple research ideas in distinct cycles.
Multi-Model Review: Gathers feedback from specified AI models for each idea.
Progress Tracking: Updates a dashboard to show the status of idea generation and review.
Use Case: A researcher needs to brainstorm novel solutions for a complex scientific problem. This Skill can generate several distinct approaches, get expert AI feedback on each, and synthesize the results into a comprehensive research document.

Quick Start

Generate and review three research ideas for the problem statement in 'research.md' using Claude Opus and GPT-4o.

Frequently Asked Questions about _generate-ideas

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

FAQPage Schema

How do I iteratively generate and refine research ideas from a problem statement?▼

Iterative idea generation works by creating multiple research ideas in distinct cycles, using multi-model reviewer feedback to ensure each new idea builds upon previous input and addresses all problem constraints.

Can I use multiple AI models to review my research ideas?▼

Yes, multi-model review gathers feedback from specified AI models for each idea. You can generate and review research ideas using models like Claude Opus and GPT-4o to synthesize comprehensive results.

What is the best way to brainstorm novel solutions for a complex scientific problem?▼

The best way to brainstorm novel solutions is to automate iterative idea generation, which creates several distinct approaches, gathers expert AI feedback on each, and synthesizes the results into a research document.

How does progress tracking work for iterative idea generation?▼

Progress tracking updates a dashboard to show the status of idea generation and review, managing progress tracking to ensure sequential completion of each idea iteration before proceeding to the next.

Do I need to provide background context for AI to generate relevant research ideas?▼

Yes, you need to provide a problem statement and background context. The iterative generation process refines research ideas based on these inputs to properly address all stated problem constraints.

When should I use automated iterative development for research idea synthesis?▼

Use automated iterative development when you need to brainstorm multiple distinct approaches for complex scientific problems and require expert AI feedback to synthesize a comprehensive research document.