spike

Validate uncertain ideas through disposable experiments before full implementation.

Updated May 9, 2026

Search Tags:#research #validation #feasibility #prototype #experiment #spike

Ready to run

npx skills add https://github.com/pmcdowall/hermes-skills --skill spike-pmcdowall

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams avoid costly implementation mistakes by testing uncertain ideas with focused, disposable experiments before committing to a full build.

Core Features & Use Cases

Feasibility Experiments: Break down ideas into targeted spikes that answer specific technical or product questions.
Approach Validation: Research competing options, build lightweight prototypes, and compare solutions before production decisions.
Use Case: When evaluating whether a new API integration, architecture choice, or user workflow is viable, use this Skill to create experiments that reveal risks and provide evidence-based recommendations.

Quick Start

Use the spike skill to validate whether this idea is feasible before starting implementation.

Frequently Asked Questions about spike

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

FAQPage Schema

How do I validate a technical idea before committing to a full build?▼

To validate a technical idea before a full build, use structured disposable experiments to test feasibility. This approach breaks down uncertain concepts into targeted research and standalone prototypes, providing evidence-based verdicts that reveal implementation risks early.

What is a spike in software engineering and when should I use it?▼

A spike in software engineering is a disposable experiment used to test the feasibility of an uncertain idea. You should use it when evaluating new API integrations, comparing architecture choices, or assessing user workflows to discover technical risks before production.

How do I compare competing technical solutions for a new feature?▼

To compare competing technical solutions for a new feature, research available options and build lightweight prototypes for each. Testing these disposable experiments yields direct comparative data, allowing you to make evidence-based decisions on which approach works best.

Can I use feasibility experiments to evaluate new API integrations?▼

Yes, you can use feasibility experiments to evaluate new API integrations. By creating targeted spikes, you can research the API, build a standalone prototype, and generate an evidence-based verdict on whether the integration is viable for your production environment.

What is the best way to reduce risks in architecture choices?▼

The best way to reduce risks in architecture choices is to run focused technical discovery experiments. By decomposing the architecture into targeted research and building standalone prototypes, you obtain evidence-based recommendations that validate the chosen approach.

When should I avoid using disposable prototypes for technical discovery?▼

You should avoid using disposable prototypes for technical discovery when an idea is already proven or requires no architectural validation. Spikes are specifically designed for uncertain ideas, so applying them to well-understood tasks wastes resources without yielding new feasibility insights.