question-resolver

Classify technical questions, investigate evidence, and document verified resolutions.

1|Updated Mar 5, 2026
One-click install
npx skills add https://github.com/baphled/dotopencode --skill question-resolver
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: question-resolver
Source: https://github.com/baphled/dotopencode/tree/main/skills/question-resolver
Command: npx skills add https://github.com/baphled/dotopencode --skill question-resolver

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of efficiently and reliably answering technical and domain-specific questions, ensuring that all inquiries are properly classified, thoroughly investigated, and their resolutions are well-documented.

Core Features & Use Cases

  • Question Classification: Determines if a question is answerable via existing documentation, requires further research (spikes/data gathering), or needs input from stakeholders.
  • Structured Investigation: Employs a methodical approach of hypothesizing, searching for evidence, and verifying findings.
  • Evidence Gathering: Prioritizes relying on verifiable sources like documentation, code, or experimental results.
  • Documentation: Records the resolved answer along with the supporting evidence.
  • Use Case: When encountering an unfamiliar API, a new codebase pattern, or ambiguous requirements, this skill provides a framework to systematically find the correct information and avoid "rabbit holes" or accepting unverified answers.

Quick Start

Use the question-resolver skill to determine if library X supports IPv6 natively and log the findings.

Frequently Asked Questions about question-resolver

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

FAQPage Schema
How do I systematically resolve technical questions without going down rabbit holes?

To systematically resolve technical questions, classify the inquiry first, then conduct a structured investigation using verifiable evidence like documentation or code, and document the final resolution. This prevents unverified assumptions and avoids rabbit holes.

What is the best way to document a research spike for an unfamiliar API?

The best way to document a research spike for an unfamiliar API is to classify the question, hypothesize, search for verifiable evidence, and record the resolved answer along with its supporting documentation to ensure findings are logged.

How do I determine if a technical question needs stakeholder input or just documentation lookup?

To determine if a technical question needs stakeholder input, classify the inquiry by checking if it is answerable via existing documentation, requires further research spikes, or explicitly needs stakeholder input to resolve ambiguous requirements.

How do I structure a technical investigation to avoid accepting unverified answers?

To structure a technical investigation and avoid unverified answers, employ a methodical approach of hypothesizing, searching for evidence in verifiable sources like code or experimental results, and verifying findings before documenting the resolution.

When should I use a structured approach for technical problem solving?

You should use a structured approach for technical problem solving when encountering unfamiliar APIs, new codebase patterns, or ambiguous requirements, ensuring answers are verifiable and properly documented rather than guessed.