spike

Validate uncertain technical ideas through focused throwaway experiments before production implementation.

Updated Feb 21, 2026

Search Tags:#research #validation #mvp #feasibility #prototype #experimentation #spike

Ready to run

npx skills add https://github.com/Gitnapp/Skills --skill spike-gitnapp

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: spike
Source: https://github.com/Gitnapp/Skills/tree/main/software-development/spike
Command: npx skills add https://github.com/Gitnapp/Skills --skill spike-gitnapp

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams reduce uncertainty before committing to production development by running focused throwaway experiments that validate feasibility and expose technical risks.

Core Features & Use Cases

Feasibility Exploration: Break broad ideas into focused validation questions and test whether critical assumptions hold.
Prototype Experiments: Build disposable spikes, compare implementation approaches, and gather evidence before engineering investment.
Use Case: A developer considering a new streaming architecture can use this Skill to test competing approaches, measure results, and decide whether the idea is ready for a real implementation.

Quick Start

Use the spike skill to validate whether my proposed feature idea is technically feasible before I start building it.

Frequently Asked Questions about spike

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

FAQPage Schema

How do I validate technical feasibility before committing to production development?▼

Spike validation uses focused throwaway experiments to test critical assumptions, comparing implementation approaches and gathering evidence to expose technical risks before engineering investment.

What is the best way to compare competing technical approaches for a new software architecture?▼

Comparing competing software approaches requires building disposable prototype spikes to measure results side-by-side, generating evidence-based verdicts on which architecture is ready for real implementation.

How do I structure a spike investigation for early-stage MVP planning?▼

Structuring a spike investigation for early-stage MVP planning involves breaking uncertain ideas into focused validation questions, testing critical assumptions through experimentation, and documenting recommendations for future builds.

Can I use throwaway experiments to reduce technical uncertainty for a proposed feature?▼

Throwaway experiments reduce technical uncertainty by validating feasibility through structured spike decomposition, lightweight prototyping, and evidence-based verdicts that expose technical risks early.

When should I not use a spike for software feasibility checks?▼

Avoid using a spike for software feasibility checks when the technical path is already certain, or when the problem requires production-grade implementation rather than disposable experimentation and evidence gathering.