researching-options

Investigate technical questions and deliver evidence-backed recommendations with a saved report.

Updated Mar 2, 2026
One-click install
npx skills add https://github.com/maestria-co/ai-playbook --skill researching-options
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: researching-options
Source: https://github.com/maestria-co/ai-playbook/tree/main/skills/researching-options
Command: npx skills add https://github.com/maestria-co/ai-playbook --skill researching-options

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Investigates a technical question and produces an opinionated recommendation with evidence. Use when: an unknown blocks planning or implementation, a library or approach needs evaluation before adoption, multiple valid options exist and a comparison is needed, or security and performance implications need assessment. Do not use when: the answer is obvious, it's an implementation detail within an already-decided approach, or it's a business/product decision.

Core Features & Use Cases

  • Define viable options and identify the tradeoffs to enable timely decisions.
  • Gather evidence across criteria such as maintenance, adoption, security, license, and fit.
  • Produce a clear, actionable recommendation and a saved report for audit.

Quick Start

Ask a scoped research question and run a timeboxed evaluation to generate a single, actionable recommendation.

Frequently Asked Questions about researching-options

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

FAQPage Schema
How do I evaluate multiple technical options before adopting a library?

Evaluating library options involves identifying viable approaches and collecting criteria-based evidence across maintenance, adoption, security, and license fit. This analysis produces an opinionated recommendation with tradeoffs clearly documented to resolve implementation blockers.

What is the best way to research an unknown technical question blocking development?

Researching a blocking technical question involves defining viable options and identifying tradeoffs to enable timely decisions. A timeboxed evaluation gathers evidence across criteria and delivers a clear, actionable recommendation saved as a report for audit.

When do I need a formal technical recommendation report?

You need a formal technical recommendation report when planning or implementation is blocked by unknowns, multiple viable options exist, or security and performance implications require assessment. It provides an audit trail for criteria-based evidence and tradeoff analysis.

Can I use evidence-based research for business or product decisions?

Evidence-based research is not suited for business or product decisions. It should only be applied when a technical unknown blocks planning, a library needs evaluation, or security and performance implications require technical assessment.

What criteria should I use to compare technical approaches?

Comparing technical approaches should use criteria such as maintenance activity, adoption rates, security vulnerabilities, licensing compatibility, and overall project fit. Gathering evidence across these dimensions enables a clear analysis of tradeoffs and an actionable recommendation.

How do I document tradeoffs when choosing between technical solutions?

Documenting tradeoffs involves analyzing collected evidence across maintenance, adoption, security, and license criteria to compare viable options. The analysis is saved into a structured .context/research/researching-options.md report to deliver a clear, actionable recommendation.