Verified:GitHub

dbs-good-question

Transform ambiguous user inquiries into structured problem specifications for agentic reasoning.

3|Updated Jun 27, 2026

Search Tags:#clarification #problem-solving #business-analysis #critical-thinking #automation-readiness #agentic-reasoning

Ready to run

npx skills add https://github.com/XinAloha/skills --skill dbs-good-question-xinaloha

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dbs-good-question
Source: https://github.com/XinAloha/skills/tree/main/methodology/good-question
Command: npx skills add https://github.com/XinAloha/skills --skill dbs-good-question-xinaloha

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the common issue of vague, poorly defined problems that prevent AI agents from providing effective solutions. It forces a transition from ambiguous complaints to structured, criticizable, and verifiable problem specifications.

Core Features & Use Cases

Problem Clarification: Identifies logical gaps, missing variables, and hidden assumptions in user queries.
Automation Readiness Assessment: Evaluates whether a task is suitable for agentic automation based on feedback loops and constraint clarity.
Use Case: When a user asks why their content isn't converting, the skill helps them define the specific funnel stage, identify the conflict between expectations and reality, and design a minimal verification experiment.

Quick Start

Use the dbs-good-question skill to analyze my current problem and help me rewrite it into a clear problem brief for an agent to solve.

Frequently Asked Questions about dbs-good-question

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

FAQPage Schema

How do I transform ambiguous business problems into structured problem specifications?▼

To transform ambiguous business problems into structured problem specifications, identify logical gaps, missing variables, and hidden assumptions to rewrite vague complaints into criticizable problem briefs. This constraint-based decomposition enables effective agentic reasoning and verification.

What is automation readiness assessment for agentic reasoning?▼

Automation readiness assessment evaluates whether a task is suitable for agentic automation based on feedback loop clarity and constraint definition. It ensures your task has the necessary structure to allow an AI agent to execute, verify, and iterate on the requested business process effectively.

How do I write a clear problem brief for an AI agent to solve?▼

Writing a clear problem brief for an AI agent requires constraint-based problem decomposition and conflict identification between expectations and reality. You must define the specific funnel stage, identify variables, and design a minimal verification experiment to guide the agent.

Can I use critical thinking to identify missing variables in content strategy analysis?▼

Yes, you can use critical thinking to identify missing variables in content strategy analysis by applying problem clarification techniques. This reveals why content is not converting by defining specific funnel stages and structuring the inquiry for actionable feedback loop design.

When do I need problem decomposition for business diagnostics?▼

You need problem decomposition for business diagnostics when facing vague, poorly defined problems that prevent AI agents from providing effective solutions. It transitions ambiguous complaints into structured, criticizable, and verifiable problem specifications across professional domains.