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Command

/reasoning-multi-path

Execute parallel reasoning exploration across multiple solution paths to find optimal approaches.

From plugin
claude-command-suite
1.3k199 skills89 agents199 commands
Install
$ npx -y skills add qdhenry/Claude-Command-Suite --agent claude-code

How it fires

How this command gets triggered: by you, by Claude, or both.

  • Fires itselfClaude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/reasoning-multi-path

Context preview

What this command does when you run it.

Execute parallel reasoning exploration across multiple solution paths to find optimal approaches.

Command definition

reasoning-multi-path.md
tools:
  - read
  - write
  - grep
  - bash
arguments: $PROBLEM

Multi-Path Reasoning

Execute parallel reasoning exploration across multiple solution paths to find optimal approaches.

Based on the WFGY project: https://github.com/onestardao/WFGY

Instructions

1. **Initialize Multi-Path Setup**

  • Parse problem from "$PROBLEM"
  • Set number of parallel paths (default: 5)
  • Load current context and constraints
  • Define exploration parameters:
  • Divergence factor: 0.3
  • Pruning threshold: 0.1
  • Max iterations: 10

2. **Generate Reasoning Paths**

  • For each path i (1 to N):
  • Apply unique perturbation V_i
  • Vary approach angle:
  • Path 1: Direct/logical
  • Path 2: Creative/lateral
  • Path 3: Systematic/methodical
  • Path 4: Analogical/comparative
  • Path 5: Contrarian/inverse
  • Maintain problem constraints
  • Track path evolution

3. **Evolve Paths Iteratively**

  • For each iteration:
  • Advance each path independently
  • Calculate path metrics:
  • Progress score
  • Confidence level
  • Semantic coherence
  • Logic consistency
  • Apply selection pressure:
  • Amplify successful paths
  • Diminish failing paths
  • Cross-pollinate insights

4. **Weight and Rank Paths**

  • Calculate path probabilities:
  • P_i = exp(-ΔS_i) / Σexp(-ΔS_j)
  • Compute dynamic weights:
  • W_i based on progress rate
  • Adjust for confidence
  • Rank by composite score:
  • Score = P_i * W_i * Confidence_i

5. **Synthesize Solutions**

  • Combine top paths weighted by score
  • Extract unique insights from each
  • Identify convergent conclusions
  • Note divergent possibilities
  • Create unified solution

Output Format

MULTI-PATH REASONING ANALYSIS
═══════════════════════════════════════
Problem: "$PROBLEM"
Paths Explored: 5
Iterations: [count]

Path Evolution:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
        Iteration
Path    1  2  3  4  5  6  7  8  9  10
────────────────────────────────────────
Path 1  ▪──●──●──●──●──●──●──●──●──●  85%
Path 2  ▪──○──●──●──●──●──●──●──○──○  72%
Path 3  ▪──○──○──●──●──●──○──○──×──×  Failed
Path 4  ▪──○──○──○──●──●──●──●──●──●  78%
Path 5  ▪──●──●──●──●──●──●──●──●──●  91%

Legend: ▪ Start ○ Exploring ● Promising × Failed

Top 3 Solution Paths:
────────────────────────────────────────

PATH 5 (Best) - Score: 0.91
Approach: [Contrarian/Inverse thinking]
Key Insight: [Main discovery]
Reasoning: [Brief explanation]
Confidence: 91%

PATH 1 - Score: 0.85
Approach: [Direct logical analysis]
Key Insight: [Main discovery]
Reasoning: [Brief explanation]
Confidence: 85%

PATH 4 - Score: 0.78
Approach: [Analogical comparison]
Key Insight: [Main discovery]
Reasoning: [Brief explanation]
Confidence: 78%

Convergent Findings:
• All paths agree: [Common conclusion 1]
• 4/5 paths suggest: [Common conclusion 2]
• Majority indicates: [Common conclusion 3]

Divergent Possibilities:
• Path 2 uniquely suggests: [Alternative]
• Path 5 contrarian view: [Opposite angle]

Synthesized Solution:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[Weighted combination of successful paths]
[Incorporating insights from all approaches]
[Final recommended solution]

Confidence: [weighted average]%
Risk Assessment: [Low/Medium/High]

Alternative Approaches:
1. If [condition], consider Path 2
2. If [constraint], prefer Path 4
3. For [scenario], Path 1 is optimal

Path Statistics:
- Average Convergence: [value]
- Cross-Path Correlation: [value]
- Solution Stability: [value]

Path Types

Logical Path

  • Step-by-step deduction
  • Rule-based reasoning
  • Systematic progression

Creative Path

  • Lateral thinking
  • Unexpected connections
  • Novel approaches

Empirical Path

  • Evidence-based
  • Data-driven
  • Experimental validation

Analogical Path

  • Pattern matching
  • Similar problem spaces
  • Transfer learning

Contrarian Path

  • Inverse thinking
  • Challenge assumptions
  • Devil's advocate

Configuration

{
  "num_paths": 5,
  "max_iterations": 10,
  "divergence_factor": 0.3,
  "pruning_threshold": 0.1,
  "selection_pressure": 0.2,
  "crossover_rate": 0.15
}

Advanced Usage

# Explore more paths
/reasoning:multi-path "problem" --paths 10

# Focus on creative solutions
/reasoning:multi-path "problem" --emphasize creative

# Quick exploration
/reasoning:multi-path "problem" --iterations 5

# Deep exploration
/reasoning:multi-path "problem" --iterations 20

Integration

Multi-path reasoning works with:

  • `/wfgy:bbpf` for path generation
  • `/semantic:node-build` to record paths
  • `/boundary:detect` to check path safety
  • `/reasoning:chain-validate` to verify logic
Read more
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