When should I invoke the deep-reason skill?

You should use it for complex tasks that require step-by-step analysis, architectural decisions, or whenever a problem affects multiple components of your system.

What makes Deep Reason different from standard Claude thinking?

Deep Reason enforces a structured workflow that separates problem definition from solution generation and uses branching to compare multiple options systematically rather than following a single linear path.

Does this skill replace the Sequential Thinking MCP?

It enhances the Sequential Thinking MCP by providing domain-specific guidelines, a structured summary template, and a specific workflow for generating project documentation.

Which model is best for the Deep Reason skill?

This skill is optimized for Claude 3.5 or 4.5 Opus models to ensure the highest quality of complex logic, synthesis, and architectural evaluation.

Can I save the analysis summary to my project files?

Yes, once the reasoning process is complete, the skill can generate a markdown summary document and save it to your project's docs or root directory.

Deep Reason Analysis

Name: Deep Reason Analysis
Author: DieGopherLT

byDieGopherLT

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생산성 및 워크플로

Facilitates structured, multi-branch sequential thinking to solve complex architectural problems and generate comprehensive analysis documentation.

소개

Deep Reason is a specialized Claude Code skill designed for high-complexity problem solving where standard responses are insufficient. It implements a rigorous sequential thinking workflow that prioritizes defining the problem space before exploring solutions. By leveraging multi-path branching and evidence gathering through MCP tools, the skill systematically evaluates multiple technical options and trade-offs. Upon completion, it provides a structured synthesis document based on a standardized template, ensuring that the logic and decisions behind significant project changes are preserved in your documentation.

주요 기능

Multi-branch exploration to compare different technical approaches
Deep tool integration for evidence-based information gathering
Structured sequential thinking workflow for high-impact decisions
Automated summary document generation using standardized templates
Isolated problem space definition to minimize solution bias
1 GitHub stars

사용 사례

Designing high-impact features with significant trade-offs and constraints
Analyzing complex system-wide bugs affecting multiple components
Evaluating major architectural refactors or technology migrations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add diegopherlt/dotclaudefiles deep-reason

For use in Claude.ai and ChatGPT

Download Skill

GitHub

소개