nina-research-decomposition

Name: nina-research-decomposition
Availability: InStock
Author: spiral-app-labs

Breaks vague research prompts into decision questions, sub-questions, evidence plans, and synthesis structure.

Updated Apr 8, 2026

Search Tags:#planning #research #evidence #deliverables #decompose #sub-questions #decision-questions

Ready to run

npx skills add https://github.com/spiral-app-labs/skills --skill nina-research-decomposition

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: nina-research-decomposition
Source: https://github.com/spiral-app-labs/skills/tree/main/nina-research-decomposition
Command: npx skills add https://github.com/spiral-app-labs/skills --skill nina-research-decomposition

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Break vague research prompts into decision questions, sub-questions, evidence plans, and synthesis structure before gathering sources.

Core Features & Use Cases

Decomposes broad prompts into a clear decision framework and research plan.
Defines evidence standards, source buckets, and expected deliverables (e.g., memo, pattern map).
Guides structured, decision-focused research for fast, high-quality outcomes.

Quick Start

Provide a structured decomposition that outlines the decision questions, sub-questions, evidence standards, and final deliverable format.

Frequently Asked Questions about nina-research-decomposition

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

FAQPage Schema

How do I break down a vague research prompt into actionable sub-questions?▼

To break down a vague research prompt, decompose it into decision questions, sub-questions, and an evidence plan before gathering sources. This structured decomposition defines the scope, sets evidence standards, and clarifies the intended final deliverable for strategic and exploratory asks.

What is a research decomposition framework for strategic decision-making?▼

A research decomposition framework transforms broad prompts into a structured plan by defining decision questions, evidence criteria, and synthesis structure. It establishes source buckets and expected deliverables, guiding structured, decision-focused research to ensure high-quality outcomes for underspecified market asks.

How to plan evidence collection and structure deliverables for exploratory research?▼

Plan evidence collection by defining specific evidence criteria and source buckets during the research decomposition phase. Structure deliverables by determining the intended final output format, such as a memo or pattern map, ensuring the gathered evidence directly addresses the key sub-questions and decision framework.

Can I use structured research planning for broad or underspecified market asks?▼

Yes, you can apply structured research planning to broad or underspecified market asks. The decomposition process translates vague prompts into a clear decision framework, outlining specific sub-questions and evidence standards to guide the research and produce a structured final deliverable.

What is the best way to define decision questions before gathering research sources?▼

The best way to define decision questions is to apply a research decomposition process that breaks the original prompt into a clear decision framework. This method identifies key sub-questions and sets evidence standards upfront, ensuring source gathering directly supports the intended synthesis structure.

Why does my exploratory research lack structure and fail to produce clear deliverables?▼

Exploratory research lacks structure when it skips decomposition, failing to establish decision questions and evidence criteria beforehand. Without defining an evidence plan and synthesis structure, broad prompts remain underspecified, preventing the creation of a clear, actionable final deliverable.