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technical-research skill

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This skill guides timeboxed technical spikes, compares options, and documents findings to support decision making in technology evaluations.

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---
name: technical-research
description: Technical spike and research investigation specialist. Use when exploring
  options for a technical decision, conducting timeboxed investigations, or evaluating
  technology choices.
author: Joseph OBrien
status: unpublished
updated: '2025-12-23'
version: 1.0.1
tag: skill
type: skill
---

# Technical Research Skill

Structured approach to technical spikes, proof of concepts, and technology evaluations.

## What This Skill Does

- Conducts timeboxed technical investigations
- Creates proof of concept implementations
- Compares technical options objectively
- Documents findings and recommendations
- Identifies risks and dependencies
- Provides implementation paths

## When to Use

- Technology selection decisions
- Architecture exploration
- Feasibility studies
- Performance investigations
- Library/framework evaluation

## Reference Files

- `references/TECHNICAL_SPIKE.template.md` - Structured spike investigation format

## Spike Structure

1. **Objective** - Clear questions to answer
2. **Timebox** - Fixed investigation period
3. **Options** - Multiple approaches explored
4. **POC** - Working code for each option
5. **Comparison** - Weighted criteria matrix
6. **Recommendation** - Justified decision

## Best Practices

- Define success criteria upfront
- Explore at least 2-3 options
- Create runnable POC code
- Document trade-offs honestly
- Track unanswered questions
- Stay within timebox

Overview

This skill packages a repeatable approach for timeboxed technical spikes, proofs of concept, and technology evaluations. It helps teams generate evidence-based recommendations and clear implementation paths. Use it to reduce uncertainty and accelerate decisions with focused research outcomes.

How this skill works

It defines a clear investigation scope with success criteria and a fixed timebox, then explores multiple technical options through runnable POC code. Each option is evaluated against weighted criteria, documented trade-offs, risks, and dependencies. The outcome is a concise recommendation and suggested implementation steps backed by evidence from the spike.

When to use it

Choosing between libraries, frameworks, or services
Validating feasibility for a new feature or integration
Exploring architectural alternatives or migration paths
Running performance or scalability investigations
Producing a decision-ready recommendation for stakeholders

Best practices

Set specific objectives and measurable success criteria before starting
Limit the investigation with a strict timebox to avoid scope creep
Evaluate at least two to three realistic options with runnable POCs
Document trade-offs, open questions, risks, and mitigation strategies
Use a weighted comparison matrix to make decisions transparent and repeatable

Example use cases

Compare two message queue systems for throughput and operational costs
Prototype an auth flow using two different identity providers and measure integration effort
Timeboxed investigation of serverless versus container deployment for cost and latency
Feasibility spike to integrate a third-party API and identify dependency risks
Create small POCs to validate performance claims of a new database technology

FAQ

How long should a typical spike be?

Keep spikes short and focused; common timeboxes are one to two weeks depending on scope and team availability.

What deliverables should the skill produce?

A brief report with objective, timebox, options explored, runnable POC links, comparison matrix, risks, unanswered questions, and a clear recommendation with next steps.