AI Logic Tree Analyst

A powerful tool for hierarchical problem analysis with AI guidance. This tool helps break down complex problems into structured logic trees, provides workflow guidance, and ensures continuous AI engagement through smart recommendations.

Main Features

• AI-Guided Workflow: Smart guidance and next-step recommendations

• Quick Analysis: Focused outputs optimized for AI consumption

• Hierarchical Structuring: Organize problems, causes, and solutions

• MECE Validation: Automatically check logical completeness

• Solution Assessment: Evaluate feasibility and priority

• Evidence-Based Reasoning: Support analysis with data and assumptions

Commands (Operations)

🚀 AI Guidance Operations (START HERE)

• get_status: Get current tree status with AI guidance and next steps

• next_steps: Get detailed workflow recommendations with specific actions

• quick_analysis: Get focused analysis results optimized for AI consumption

📝 Basic Operations

• add_node: Create a new node in the tree

• update_node: Modify existing node content or metadata

• remove_node: Delete a node and all descendants

• visualize_tree: Display the complete tree structure

🔍 Advanced Analysis

• analyze_tree: Comprehensive analysis with MECE validation

• generate_hypotheses: Generate testable hypotheses for a node

• suggest_actions: Get prioritized action recommendations

AI Workflow Integration

For continuous AI engagement, ALWAYS use these operations:

1. Start any session: {"operation": "get_status"}

   • Gets current state and what to do next

   • Provides AI guidance for next steps

2. After each major action: {"operation": "quick_analysis"}

   • Gets focused insights without overwhelming output

   • Tells AI exactly what to do next

3. When unsure: {"operation": "next_steps"}

   • Gets specific parameter templates

   • Shows complete workflow guidance

Streamlined Parameter Usage

Simple node creation: {"operation": "add_node", "content": "Your problem", "nodeType": "problem"}

With metadata (for solutions): {"operation": "add_node", "content": "Solution", "nodeType": "solution", "parentId": "node_1", "metadata": {"priority": 4, "feasibility": 3}}

Check what to do next: {"operation": "get_status"}

Example AI Session

Start (ALWAYS begin with this): {"operation": "get_status"}

Response includes: current state, AI guidance, suggested next operations

If tree is empty, AI will be guided to: {"operation": "add_node", "content": "Low website conversion", "nodeType": "problem"}

After adding nodes, check progress: {"operation": "quick_analysis"}

Response: focused insights, key findings, next actions, AI guidance

Get specific next steps: {"operation": "next_steps"}

Response: exact parameters to use, workflow guidance, reasoning

This design ensures AI continues using the tool by providing clear guidance and focused outputs.