spike

Name: spike
Availability: InStock
Author: mark

Decompose ideas into testable spikes and validate feasibility with experiments.

31|3|Updated May 7, 2026

Search Tags:#planning #feasibility #prototype #experimentation #spike #rapid-learning

Ready to run

npx skills add https://github.com/markwang2658/hermes-windows-native --skill spike-markwang2658

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: spike
Source: https://github.com/markwang2658/hermes-windows-native/tree/main/hermes-agent/skills/software-development/spike
Command: npx skills add https://github.com/markwang2658/hermes-windows-native --skill spike-markwang2658

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Spikes provide a lightweight, disposable approach to validate ideas before committing to a full build. They help surface feasibility, required research, and potential risks early, saving time and resources.

Core Features & Use Cases

Decompose an idea into 2–5 independent feasibility questions, each tackled as a separate spike.
Align & Decide on ordering, scope, and acceptance criteria before any implementation.
Demonstrate outcomes with observable results, verdicts, and learnings to guide real development.

Quick Start

Perform a quick idea-to-spike workflow by decomposing the concept into 2–5 feasibility questions and running targeted experiments to gather learnings.

Frequently Asked Questions about spike

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

FAQPage Schema

What is a spike in software engineering and when should I use this feasibility testing approach?▼

A spike is a throwaway experiment used to validate ideas and test feasibility fast. Use this rapid-learning approach for early-stage tasks where quick, iterative experiments determine the viability of an approach before committing to a full build.

How do I decompose an idea into testable spikes for rapid prototyping?▼

To decompose an idea into testable spikes, break the concept down into 2 to 5 independent feasibility questions. Each question is tackled as a separate spike, allowing you to align on ordering, scope, and acceptance criteria before any implementation begins.

What is the best way to structure throwaway experiments to validate technical feasibility?▼

The best way to structure throwaway experiments is to apply a workflow that requires a clear decomposition step, lightweight execution artifacts, and a concise verdict write-up. This demonstrates outcomes with observable results and learnings to guide real development.

Can I use rapid-learning spikes to evaluate risks before starting full implementation?▼

Yes, you can use rapid-learning spikes to evaluate risks early. Spikes provide a lightweight, disposable approach to surface feasibility, required research, and potential risks before committing resources, saving time by validating approaches upfront.

When should I avoid using disposable prototype experiments for project validation?▼

You should avoid using disposable prototype experiments when a task is not early-stage or lacks clear decomposition steps. Spikes require structuring ideas into discrete, testable questions, so they are less suited for tasks with predetermined approaches or no independent feasibility variables.