Files
APAW/.kilo/workflows/evaluator-optimizer.md
¨NW¨ fbc1f6122f feat: add workflow templates for research patterns
Implemented workflow templates based on Anthropic research:

- parallel-review.md: Parallel execution of security + performance reviews
- evaluator-optimizer.md: Iterative improvement loop (code-skeptic → the-fixer)
- chain-of-thought.md: Sequential step decomposition with gates

Each template includes:
- Pattern overview and implementation
- Execution flow diagram
- Benefits and configuration
- Usage examples

Related: Issues #21, #22 - Patterns from research
Milestone: #47 Cognitive Enhancement
2026-04-05 02:09:40 +01:00

2.5 KiB

Evaluator-Optimizer Workflow

Implements the Evaluator-Optimizer pattern from Anthropic research.

Overview

Iterative improvement loop: evaluator reviews, optimizer improves, repeat until convergence.

Pattern

def evaluator_optimizer_loop(code, max_iterations=3):
    """
    Evaluator-Optimizer pattern for code review.
    From Anthropic: "One LLM call generates a response while 
    another provides evaluation and feedback in a loop."
    """
    
    for iteration in range(max_iterations):
        # Evaluator reviews
        evaluation = Task(
            subagent_type="code-skeptic",
            prompt=code
        )
        
        if evaluation.verdict == "APPROVED":
            return {"success": True, "iterations": iteration}
        
        # Optimizer fixes
        fixes = Task(
            subagent_type="the-fixer",
            issues=evaluation.issues,
            code=code
        )
        
        code = apply_fixes(code, fixes)
    
    return {"success": False, "iterations": max_iterations}

Execution Flow

[Code Submitted]
       ↓
[Evaluator: code-skeptic]
       ↓
┌─────────────────────┐
│                     │
│ [APPROVED] ──Yes──→ [PASS]
│                     │
│ [CHANGES] ──No───→ [Optimizer: the-fixer]
│                     │
│                     ↓
│              [Apply Fixes]
│                     │
│                     ↓
│              [Iterations < Max?]
│                Yes      No
│                 ↓        ↓
│              [Loop]  [Escalate]
└─────────────────────┘

Benefits

  • Convergence Guarantee: Maximum iterations prevent infinite loops
  • Quality Improvement: Each iteration improves code
  • Iterative Feedback: Evaluators teach optimizers

Configuration

# .kilo/config/evaluator-optimizer.yaml

iteration_loops:
  code_review:
    evaluator: code-skeptic
    optimizer: the-fixer
    max_iterations: 3
    convergence: all_issues_resolved
  
  security_review:
    evaluator: security-auditor
    optimizer: the-fixer
    max_iterations: 2
    convergence: no_critical_vulnerabilities

Usage

/workflow evaluator-optimizer --issue 42 --max-iterations 3

Scoring

Iterations Score Impact
1 Perfect (10/10)
2 Good (8/10)
3 Acceptable (7/10)
>3 Poor (triggers prompt-optimizer)