When should I use the Deep Problem Analysis skill?

You should activate this skill when a problem is ambiguous, has multiple competing solutions, or involves high-stakes architectural decisions where the cost of a wrong choice is high.

Can this skill help with legacy code refactoring?

Yes, it is excellent for analyzing complex legacy systems to understand dependencies and risks before proposing a modernization or refactoring strategy.

How does this skill prevent 'analysis paralysis'?

The skill includes specific 'When NOT to Use' criteria, ensuring it stays inactive for straightforward, well-defined tasks while providing a time-boxed, structured path for complex ones.

What is the benefit of the 'Multi-Perspective Analysis' feature?

It ensures that solutions aren't just technically sound, but also align with user needs, business goals, and long-term maintenance requirements.

Deep Problem Analysis

Name: Deep Problem Analysis
Author: rysweet

byrysweet

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Productivity & Workflow

Performs systematic, multi-perspective analysis to resolve complex architectural and logical challenges using structured thinking methodologies.

About

The Deep Problem Analysis skill (meta-cognitive) provides Claude with a rigorous framework for tackling ambiguous, high-stakes, or complex coding problems. Instead of jumping straight to implementation, this skill activates a multi-stage 'ultrathink' process that clarifies requirements, decomposes subproblems, surfaces hidden assumptions, and evaluates solutions through detailed tradeoff matrices. It is an essential tool for senior-level architectural decision-making, helping developers avoid premature solutions and identify the most robust path forward before a single line of code is written.

Key Features

Hidden assumption surfacing and critical risk assessment
Comprehensive solution comparison via detailed tradeoff matrices
Multi-perspective analysis covering Technical, Business, User, and Maintenance angles
First-principles thinking and inversion-based failure analysis
Structured problem decomposition and initial clarification prompts
17 GitHub stars

Use Cases

Evaluating and choosing between competing database technologies or frameworks
Conducting project pre-mortems to identify and mitigate potential points of failure
Resolving contradictory requirements in complex feature requests

About

Key Features

Hidden assumption surfacing and critical risk assessment
Comprehensive solution comparison via detailed tradeoff matrices
Multi-perspective analysis covering Technical, Business, User, and Maintenance angles
First-principles thinking and inversion-based failure analysis
Structured problem decomposition and initial clarification prompts
17 GitHub stars

Use Cases

Evaluating and choosing between competing database technologies or frameworks
Conducting project pre-mortems to identify and mitigate potential points of failure
Resolving contradictory requirements in complex feature requests