moai-workflow-thinking

Automate structured step-by-step reasoning for architecture decisions and complex analyses.

Updated Apr 26, 2026

Search Tags:#workflow #MCP #architecture-decision #sequential-thinking #deepthink

Ready to run

npx skills add https://github.com/gkswls5006-web/last-todo --skill moai-workflow-thinking-gkswls5006-web

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: moai-workflow-thinking
Source: https://github.com/gkswls5006-web/last-todo/tree/main/.claude/skills/moai-workflow-thinking
Command: npx skills add https://github.com/gkswls5006-web/last-todo --skill moai-workflow-thinking-gkswls5006-web

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Structured, step-by-step reasoning helps Claude perform deep analysis and make architecture decisions more transparent and auditable.

Core Features & Use Cases

Three distinct reasoning modes with explicit triggers and MCP tooling for complex problems.
Activation patterns and tool parameter guidance to orchestrate multi-step analyses across files and components.
Useful for architecture decisions, technology selection, and trade-off evaluations where traceable reasoning is required.

Quick Start

Initiate the model with a complex problem and prompt it to perform sequential thinking using --deepthink for architecture decisions.

Frequently Asked Questions about moai-workflow-thinking

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

FAQPage Schema

How do I use sequential thinking for architecture decisions?▼

Sequential thinking for architecture decisions automates structured, step-by-step reasoning to make complex analyses transparent and auditable. You initiate the model with a complex problem and prompt it to perform sequential thinking using --deepthink for multi-file design scenarios.

What is structured reasoning for technology selection?▼

Structured reasoning for technology selection is a step-by-step analysis process that provides traceable reasoning traces for trade-off evaluations. It uses explicit thinking modes and MCP-based tooling to orchestrate multi-step analyses across files and components.

Does MCP-based tooling work with multi-file design scenarios?▼

Yes, MCP-based tooling works with multi-file design scenarios by applying activation patterns and tool parameter guidance to orchestrate analyses. This ensures clear reasoning traces are maintained across multiple components during architecture evaluations.

When do I need traceable reasoning traces for trade-off analyses?▼

You need traceable reasoning traces for trade-off analyses when evaluating complex technology selections where transparent, auditable decisions are required. This approach satisfies explicit thinking modes and MCP-based tool usage to ensure clear reasoning steps across components.

Can I use deepthink mode for complex problem analysis?▼

Yes, you can use deepthink mode for complex problem analysis by initiating the model and prompting it to perform sequential thinking. This triggers distinct reasoning modes with explicit triggers and MCP tooling for structured multi-file design evaluation.

What are the limitations of sequential thinking in architecture decisions?▼

Sequential thinking in architecture decisions is limited by its reliance on explicit triggers and MCP-based tool usage defined in the frontmatter. It requires complex problem inputs to properly activate its three distinct reasoning modes for multi-file trade-off evaluations.