Reasoner - Advanced Multi-Strategy Reasoning

Core Concept

mcp__plugin_kg_kodegen__reasoner provides sophisticated reasoning with multiple search strategies. Unlike sequential_thinking (simple linear tracking), reasoner uses algorithms like Beam Search and Monte Carlo Tree Search (MCTS) to explore and score multiple solution paths, finding optimal reasoning chains.

Strategies

| Strategy | Best For | Description | |----------|----------|-------------| | beam_search | General problems | Maintains top N paths simultaneously | | mcts | Decision trees | UCB1/PUCT exploration-exploitation | | mcts_002_alpha | Creative solutions | 10% higher exploration bonus | | mcts_002alt_alpha | Detailed analysis | Rewards longer reasoning paths |

Key Parameters

Required: | Parameter | Type | Description | |-----------|------|-------------| | thought | string | Current reasoning step | | thought_number | number | Current step (1-based) | | total_thoughts | number | Estimated total needed | | next_thought_needed | boolean | Whether more steps needed |

Optional: | Parameter | Type | Description | |-----------|------|-------------| | strategy_type | string | beam_search (default), mcts, mcts_002_alpha, mcts_002alt_alpha | | beam_width | number | Paths to maintain (1-10, default: 3) | | num_simulations | number | MCTS rollouts (1-150, default: 50) | | parent_id | string | Parent node for branching |

Usage Examples

Beam Search (Default)

{
  "thought": "Analyzing possible caching strategies for the API",
  "thought_number": 1,
  "total_thoughts": 4,
  "next_thought_needed": true,
  "strategy_type": "beam_search",
  "beam_width": 3
}

MCTS for Decision Making

{
  "thought": "Evaluating database migration approaches",
  "thought_number": 1,
  "total_thoughts": 3,
  "next_thought_needed": true,
  "strategy_type": "mcts",
  "num_simulations": 100
}

Creative Problem Solving

{
  "thought": "Exploring novel approaches to distributed consensus",
  "thought_number": 1,
  "total_thoughts": 5,
  "next_thought_needed": true,
  "strategy_type": "mcts_002_alpha",
  "num_simulations": 75
}

Detailed Analysis

{
  "thought": "Deep comparison of microservices vs monolithic architecture",
  "thought_number": 1,
  "total_thoughts": 6,
  "next_thought_needed": true,
  "strategy_type": "mcts_002alt_alpha",
  "num_simulations": 50
}

Branching from Parent

{
  "thought": "Alternative approach using event sourcing",
  "thought_number": 3,
  "total_thoughts": 5,
  "next_thought_needed": true,
  "parent_id": "previous-node-uuid"
}

Output Format

{
  "session_id": "uuid-v4",
  "thought": "echoed input",
  "score": 0.85,
  "depth": 2,
  "is_complete": false,
  "next_thought_needed": true,
  "branches": 3,
  "best_path_score": 0.92,
  "strategy": "beam_search",
  "history_length": 5
}

When to Use What

| Problem Type | Tool | Why | |--------------|------|-----| | Simple step-by-step | sequential_thinking | No scoring needed | | Optimization | reasoner (mcts) | Finds optimal path | | Multiple alternatives | reasoner (beam_search) | Tracks top N paths | | Creative exploration | reasoner (mcts_002_alpha) | Higher exploration | | Detailed analysis | reasoner (mcts_002alt_alpha) | Rewards depth |

Reasoner vs Sequential Thinking

| Feature | Sequential Thinking | Reasoner | |---------|-------------------|----------| | Path scoring | No | Yes (0.0-1.0) | | Strategy selection | No | beam_search, MCTS variants | | Semantic analysis | No | Yes (Stella 400M embeddings) | | Best path tracking | No | Yes (best_path_score) | | Complexity | Lower | Higher | | Use case | Linear reasoning | Optimization/exploration |

Remember

• Choose strategy wisely - beam_search for general, MCTS for optimization
• Adjust beam_width - higher = more paths but slower
• num_simulations - more = better MCTS results but slower
• Check scores - output includes quality scores (0.0-1.0)
• Use for complex problems - overkill for simple reasoning
• Prefer sequential_thinking for straightforward step-by-step