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Deliberate Reasoning Engine (DRE)

โ˜… 5

from haasonsaas

Transforms linear AI reasoning into structured, auditable thought graphs, enabling language models to externalize their reasoning process as a directed acyclic graph (DAG).

๐Ÿ”ฅ๐Ÿ”ฅ๐Ÿ”ฅโœ“ VerifiedFreeQuick setup

Deliberate Reasoning Engine (DRE)

A Model Context Protocol (MCP) server that transforms linear AI reasoning into structured, auditable thought graphs. DRE enables Language Models to externalize their reasoning process as a directed acyclic graph (DAG) with semantic thought types, dependencies, and validation.

๐ŸŒŸ Features

  • ๐Ÿง  Semantic Thought Types: Categorize thoughts as Objectives, Hypotheses, Assumptions, Questions, Evidence, Actions, Synthesis, and Critiques
  • ๐Ÿ”— Graph-Based Dependencies: Build a DAG of thoughts with explicit relationships and dependencies
  • ๐Ÿšจ Assumption Tracking: Monitor and invalidate assumptions with automatic cascade to dependent thoughts
  • ๐Ÿ“Š Hypothesis Scoring: Track supporting and contradicting evidence (coming soon)
  • ๐Ÿ’พ Session Persistence: Save and load reasoning sessions (coming soon)
  • โœ… Graph Validation: Detect cycles, contradictions, and orphaned thoughts
  • ๐ŸŽฏ Focused Reasoning: Keep LLMs on track with structured problem decomposition

๐Ÿ› ๏ธ Available Tools

log_thought

Log a structured thought with semantic type and dependencies.

Parameters:

  • thought (string, required): The content of the thought
  • thought_type (enum, required): One of:
    • objective: The overall goal of the reasoning task
    • hypothesis: A proposed explanation or solution
    • assumption: A belief taken as true for this reasoning line
    • question: A point of uncertainty to resolve
    • sub_problem: Decomposition of a larger problem
    • evidence: Data from tools or prior knowledge
    • action: A plan to use a tool
    • synthesis: A conclusion from previous thoughts
    • critique: Self-correction or flaw identification
  • dependencies (string[], optional): IDs of thoughts this depends on
  • confidence (number 0-1, optional): Confidence level
  • action_request (object, optional): Tool and parameters to execute

get_thought_graph

Retrieve the current reasoning graph.

Parameters:

  • format (enum, optional): "full" or "summary" (default: "summary")

invalidate_assumption

Mark an assumption as invalid, cascading to all dependent thoughts.

Parameters:

  • thought_id (string, required): ID of the assumption to invalidate
  • reason (string, required): Explanation for invalidation

๐Ÿ—๏ธ Architecture

DRE models reasoning as a directed acyclic graph where:

  • Nodes are thoughts with semantic types
  • Edges represent dependencies between thoughts
  • Status tracking (active/stale) enables dynamic reasoning updates
  • Cascade invalidation ensures reasoning consistency

๐Ÿค Use Cases

  • Strategic Decision Making: Break down complex business decisions
  • Research Planning: Structure research questions and hypotheses
  • Problem Solving: Decompose problems into manageable sub-problems
  • Risk Analysis: Track assumptions and their implications
  • Debugging: Systematic root cause analysis
  • Learning: Structured exploration of new topics

๐Ÿ”ง Development

# Install dependencies
npm install

# Build TypeScript
npm run build

# Run in development mode
npm run dev

# Run tests
npm test

๐Ÿ“ Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

๐Ÿ“„ License

MIT - see LICENSE for details.

๐Ÿ™ Acknowledgments

  • Built on the Model Context Protocol
  • Inspired by structured reasoning systems and cognitive architectures
  • Thanks to Anthropic for Claude and the MCP specification

๐Ÿšฆ Roadmap

  • Hypothesis scoring based on evidence
  • Session persistence and resumption
  • Graph visualization export
  • Conflict detection between branches
  • Integration with external reasoning tools
  • Multi-agent reasoning support

๐Ÿ“Š Stats