ln-spike

Conduct time-boxed technical investigations and record structured verdicts.

7|Updated Mar 16, 2026
One-click install
npx skills add https://github.com/hashintel/brunch --skill ln-spike
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ln-spike
Source: https://github.com/hashintel/brunch/tree/main/.agents/skills/ln-spike
Command: npx skills add https://github.com/hashintel/brunch --skill ln-spike

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

It enables quick, temporary investigations to clarify complex technical questions, reducing uncertainty before making commitments.

Core Features & Use Cases

  • Focused Investigations: Conduct time-boxed research to answer specific technical questions.
  • Knowledge Capture: Record verdicts, approaches, and recommendations for future reference.
  • Use Case: When encountering a challenging algorithm choice, run a spike to determine its feasibility and impact, then document findings for team review.

Quick Start

Ask the AI to investigate a technical question, using the structured verdict template provided above.

Frequently Asked Questions about ln-spike

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

FAQPage Schema
What is a technical spike for resolving software development uncertainty?

A technical spike is a rapid, time-boxed investigation method used to clarify complex technical questions and reduce uncertainty before making architectural or algorithmic commitments.

When should I run a spike investigation during architecture validation?

Run a spike investigation when encountering challenging algorithm choices or technical uncertainties, ensuring feasibility and impact are determined before committing to a specific software architecture.

How do I conduct a time-boxed technical investigation for a complex algorithm choice?

Conduct a time-boxed technical investigation by asking the AI to investigate the specific question, documenting approaches and recommendations using a structured verdict template for team review.

How are investigation findings and verdicts captured for future reference?

Investigation findings, verdicts, and recommendations are captured by automatically updating knowledge bases and decision documents, ensuring full traceability for future team reference.

Can I use this structured investigation approach for research outside of software development?

Yes, this structured investigation approach applies across software development, research, and architecture validation scenarios, making it suitable for resolving technical uncertainties in various domains.

What is the best way to document technical decisions and reduce uncertainty before committing?

The best way to reduce uncertainty is running focused, structured technical investigations that record verdicts and approaches, automatically updating decision documents to ensure traceability and team alignment.