openclaw - 💡(How to fix) Fix [Feature Request] Genetic Template System - Inheritance, Crossover, and Mutation for Agent Configurations [1 participants]

interface TemplateGene {
  id: string;
  parentId?: string;           // Inherit from parent template
  traits: {
    systemPrompt: string;
    temperature: number;
    maxTokens: number;
    tools: string[];
    sandbox?: SandboxConfig;
  };
  fitness?: number;            // Performance score for selection
}

---

{
  "id": "writer-v2",
  "parentId": "writer-v1",
  "traits": {
    "systemPrompt": "{{parent.systemPrompt}}\n\nAdditional: Focus on clarity.",
    "temperature": 0.8
  }
}

---

function crossover(parent1: TemplateGene, parent2: TemplateGene): TemplateGene {
  return {
    id: generateId(),
    parentId: null,
    traits: {
      systemPrompt: crossoverPrompts(parent1, parent2),
      temperature: randomChoice([parent1.traits.temperature, parent2.traits.temperature]),
      maxTokens: average([parent1.traits.maxTokens, parent2.traits.maxTokens]),
      tools: union([parent1.traits.tools, parent2.traits.tools])
    }
  };
}

---

function mutate(template: TemplateGene, mutationRate: number): TemplateGene {
  const mutated = deepClone(template);
  
  if (Math.random() < mutationRate) {
    // Mutate temperature
    mutated.traits.temperature += (Math.random() - 0.5) * 0.2;
  }
  
  if (Math.random() < mutationRate) {
    // Mutate prompt - add/remove/modify sections
    mutated.traits.systemPrompt = mutatePrompt(mutated.traits.systemPrompt);
  }
  
  return mutated;
}

---

interface FitnessMetrics {
  successRate: number;         // Task completion rate
  avgResponseTime: number;     // Speed
  userSatisfaction: number;    // Feedback score
  tokenEfficiency: number;     // Output quality per token
}

function calculateFitness(metrics: FitnessMetrics): number {
  return (
    metrics.successRate * 0.4 +
    metrics.userSatisfaction * 0.3 +
    metrics.tokenEfficiency * 0.2 +
    (1 / metrics.avgResponseTime) * 0.1
  );
}

---

Generation 1: Basic writer template
    ↓ (mutation + selection)
Generation 2: Writer with better hooks
    ↓ (crossover with editor template)
Generation 3: Writer with self-editing capability
    ↓ (continued evolution)
Generation N: Highly optimized article writer

---

Secretory template × Writer template
    ↓ (crossover)
Coordinator template with writing skills

---

Original prompt: "Write an article"
    ↓ (mutation)
Variant A: "Write an engaging article with hooks"
Variant B: "Write a concise article with data"
    ↓ (selection based on performance)
Winner: "Write an engaging, data-backed article with hooks"

---

# Create template variant
openclaw template mutate writer-iso --rate 0.1 --output writer-v2

# Crossover two templates
openclaw template crossover writer-iso editor-iso --output hybrid-writer

# View template lineage
openclaw template lineage writer-v3

# Run evolutionary cycle
openclaw evolve --generations 10 --population 5 --template writer-iso

---

{
  "geneticTemplates": {
    "enabled": true,
    "templates": {
      "writer-v1": {
        "fitness": 0.85,
        "generation": 1,
        "traits": { ... }
      },
      "writer-v2": {
        "parentId": "writer-v1",
        "fitness": 0.92,
        "generation": 2,
        "mutations": ["temperature+0.1", "prompt+clarity"]
      }
    },
    "evolution": {
      "mutationRate": 0.1,
      "crossoverRate": 0.3,
      "selectionPressure": 0.5,
      "populationSize": 10
    }
  }
}