research-craft

Guide research planning, experiment design, and research log maintenance.

50|3|Updated Jun 15, 2026
One-click install
npx skills add https://github.com/nik1t7n/research-craft-skill --skill research-craft-nik1t7n
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research-craft
Source: https://github.com/nik1t7n/research-craft-skill/tree/main
Command: npx skills add https://github.com/nik1t7n/research-craft-skill --skill research-craft-nik1t7n

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of turning vague research work into a structured, actionable process, improving problem selection, input quality, and overall research effectiveness.

Core Features & Use Cases

  • Problem Selection: Guide users in choosing problems based on their relevance and feasibility.
  • Input Improvement: Help users upgrade their research inputs with a focus on primary sources and diverse perspectives.
  • Experiment Design: Assist in creating clear, testable experiments with defined outcomes.
  • Log Keeping: Provide a framework for maintaining a research log for accountability and learning.
  • Output Analysis: Guide users in interpreting results and adjusting their research approach accordingly.
  • Use Case: When designing an AI/ML experiment, this Skill helps set up a clear research plan with defined outcomes, input upgrades, and a structured log for tracking progress.

Quick Start

Start using the research-craft skill by initiating a new research project and following the provided guidelines.

Frequently Asked Questions about research-craft

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

FAQPage Schema
How do I structure a vague AI/ML research problem into an actionable workflow?

To structure AI/ML research, you need a workflow that guides problem selection based on relevance and feasibility. This approach transforms vague ideas into actionable plans with defined outcomes and structured logs for tracking progress.

What is the best way to design testable experiments with clear outcomes?

The best way to design experiments is using a structured methodology that assists in creating clear, testable setups with defined outcomes. This ensures your research inputs are upgraded with primary sources and diverse perspectives for reliable results.

How do I improve research inputs using primary sources and diverse perspectives?

Improving research inputs requires a framework that focuses on upgrading data with primary sources and diverse perspectives. This enhances the overall quality and effectiveness of your structured research workflow before experiment execution.

Why do I need to maintain a research log for AI/ML experiment accountability?

You need a research log to maintain accountability and facilitate learning throughout your workflow. It provides a structured framework for tracking experiment progress, interpreting output analysis results, and adjusting your research approach accordingly.

Can I use this structured research methodology for team projects?

Yes, this structured research methodology is designed for individuals and teams conducting research in various fields. It guides collaborative problem selection, input improvement, experiment design, and shared log keeping for comprehensive team alignment.

When should I adjust my research approach based on output analysis?

You should adjust your research approach during output analysis when interpreting results reveals new insights. This workflow guides you in evaluating defined outcomes and modifying your experiment design to maintain research effectiveness.