@holoscript/ai-validator

@holoscript/ai-validator

AI hallucination validation layer for HoloScript. Prevents invalid AI-generated code from breaking user workflows by detecting common LLM hallucination patterns.

Features

• ✅ Multi-Strategy Validation - Syntax, semantic, structural, and trait validation
• ✅ Hallucination Detection - Detects 10+ common LLM hallucination patterns
• ✅ Provider-Specific Rules - Custom validation for OpenAI, Anthropic, Gemini
• ✅ Detailed Error Reports - Line numbers, suggestions, severity levels
• ✅ Trait Similarity Matching - Suggests correct traits for typos
• ✅ Configurable Thresholds - Adjustable hallucination score limits
• ✅ 80%+ Test Coverage - Production-ready with comprehensive tests

Installation

pnpm add @holoscript/ai-validator

Quick Start

import { AIValidator } from '@holoscript/ai-validator';

const validator = new AIValidator({
  hallucinationThreshold: 50,
  provider: 'anthropic',
  strict: false,
});

// Validate AI-generated code
const result = await validator.validate(aiGeneratedCode);

if (!result.valid) {
  console.error('Validation failed:');
  result.errors.forEach((err) => {
    console.log(`[${err.severity}] ${err.message}`);
    if (err.suggestion) {
      console.log(`  Suggestion: ${err.suggestion}`);
    }
  });
} else {
  console.log(`✓ Valid code (hallucination score: ${result.metadata.hallucinationScore}/100)`);
}

API Reference

AIValidator

Main validation class with configurable rules.

Constructor Options

interface ValidatorConfig {
  strict?: boolean; // Reject warnings as errors (default: false)
  knownTraits?: string[]; // Custom trait registry
  hallucinationThreshold?: number; // Max hallucination score 0-100 (default: 50)
  detectHallucinations?: boolean; // Enable pattern detection (default: true)
  provider?: 'openai' | 'anthropic' | 'gemini' | 'local' | 'unknown';
}

Methods

validate(code: string): Promise<ValidationResult>

Validates HoloScript code and returns detailed results.

const result = await validator.validate(code);

console.log('Valid:', result.valid);
console.log('Errors:', result.errors.length);
console.log('Warnings:', result.warnings.length);
console.log('Hallucination Score:', result.metadata.hallucinationScore);

getStats(): ValidatorStats

Returns validation statistics.

const stats = validator.getStats();
console.log('Known traits:', stats.knownTraits);
console.log('Hallucination patterns:', stats.hallucinationPatterns);

validateAICode(code, config?)

Convenience function for one-off validation.

import { validateAICode } from '@holoscript/ai-validator';

const result = await validateAICode(aiCode, {
  provider: 'openai',
  hallucinationThreshold: 60,
});

Validation Strategies

1. Syntax Validation

Validates code against HoloScript parser:

// ❌ Invalid: Triple braces
cube {{{
  @color(red)
}}}

// ✅ Valid: Correct syntax
cube {
  @color(red)
}

2. Structural Validation

Checks balanced braces and proper nesting:

// ❌ Invalid: Unclosed brace
cube {
  @color(red)

// ✅ Valid: Balanced
cube {
  @color(red)
}

3. Trait Validation

Ensures traits exist in known registry:

// ❌ Invalid: Unknown trait
cube {
  @magic_flying
  @ai_powered
}

// ✅ Valid: Known traits
cube {
  @grabbable
  @physics
}

4. Hallucination Detection

Detects common LLM hallucination patterns:

Pattern	Score	Example
AI-like traits	30	@ai_powered, @smart_detection
Triple braces	50	{{{ or }}}
OOP syntax	40	class, extends, implements
Placeholders	60	[PLACEHOLDER], [YOUR_VALUE]
Task-marker comments	20	Line comments starting with common task labels
HTML/XML	35	<cube>...</cube>
JavaScript	35	function createCube()
Template literals	45	@color("${variable}")
Excessive repetition	25	5+ identical traits

5. Semantic Validation

Warns about style and performance issues:

// ⚠️ Warning: Empty object
cube {
}

// ⚠️ Warning: Very long line
cube { @position(0, 0, 0, 0, 0, 0, ...[100 values]...) }

Provider-Specific Validation

OpenAI (GPT-4, GPT-3.5)

Detects markdown code fences:

const validator = new AIValidator({ provider: 'openai' });

// ❌ Invalid: Markdown fences
```holoscript
cube { @color(red) }

// ✅ Valid: No fences cube { @color(red) }

### Anthropic (Claude)

Allows explanatory comments:

```typescript
const validator = new AIValidator({ provider: 'anthropic' });

// ✅ Valid: Claude-style comments allowed
cube {
  // This is a red cube
  @color(red)
}

Hallucination Score

The validator calculates a hallucination score (0-100) based on detected patterns:

• 0-20: Very likely valid code
• 20-40: Possibly valid, minor issues
• 40-60: Suspicious patterns detected
• 60-80: Likely hallucinated
• 80-100: Almost certainly hallucinated

const result = await validator.validate(suspiciousCode);

if (result.metadata.hallucinationScore > 70) {
  // Regenerate with stricter constraints
  regenerateCode({ moreStrict: true });
}

Integration Examples

With MCP Server

import { AIValidator } from '@holoscript/ai-validator';

const validator = new AIValidator({
  provider: 'anthropic',
  hallucinationThreshold: 50,
});

// In MCP tool handler
async function handleGenerateObject(args: any) {
  const generatedCode = await generateWithLLM(args.prompt);

  const validation = await validator.validate(generatedCode);

  if (!validation.valid) {
    // Provide feedback to LLM for regeneration
    const feedback = validation.errors.map((e) => e.message).join('\n');
    return await generateWithLLM(args.prompt, { feedback });
  }

  return generatedCode;
}

With Security Sandbox

import { AIValidator } from '@holoscript/ai-validator';
import { HoloScriptSandbox } from '@holoscript/security-sandbox';

const validator = new AIValidator();
const sandbox = new HoloScriptSandbox();

// Validate THEN sandbox
async function executeSafely(aiCode: string) {
  // Step 1: Validate
  const validation = await validator.validate(aiCode);
  if (!validation.valid) {
    throw new Error(`Invalid code: ${validation.errors[0].message}`);
  }

  // Step 2: Sandbox
  const result = await sandbox.executeHoloScript(aiCode, {
    source: 'ai-generated',
  });

  return result;
}

Feedback Loop

async function generateWithValidation(prompt: string, maxAttempts = 3) {
  for (let i = 0; i < maxAttempts; i++) {
    const code = await llm.generate(prompt);
    const validation = await validator.validate(code);

    if (validation.valid) {
      return code;
    }

    // Provide validation feedback to LLM
    const feedback = [
      'Your previous attempt had errors:',
      ...validation.errors.map((e) => `- ${e.message}`),
      ...validation.errors.map((e) => (e.suggestion ? `  Try: ${e.suggestion}` : '')),
    ].join('\n');

    prompt = `${prompt}\n\nFeedback from previous attempt:\n${feedback}`;
  }

  throw new Error('Failed to generate valid code after max attempts');
}

Best Practices

1. Set Appropriate Thresholds

// Strict for production
const prodValidator = new AIValidator({
  hallucinationThreshold: 30,
  strict: true,
});

// Lenient for development
const devValidator = new AIValidator({
  hallucinationThreshold: 70,
  strict: false,
});

2. Provider Hints

// Set provider for better validation
const validator = new AIValidator({
  provider: detectProvider(apiKey), // 'openai', 'anthropic', etc.
});

3. Custom Trait Registry

// Add custom traits for domain-specific validation
const validator = new AIValidator({
  knownTraits: [...DEFAULT_TRAITS, '@custom_physics', '@special_rendering'],
});

4. Error Reporting

const result = await validator.validate(code);

if (!result.valid) {
  // Log for debugging
  console.error('Validation errors:', result.errors);

  // Send to monitoring
  monitoring.trackValidationFailure({
    provider: result.metadata.provider,
    hallucinationScore: result.metadata.hallucinationScore,
    errors: result.errors.length,
  });

  // Provide user feedback
  showUserError('Generated code was invalid. Please try again.');
}

License

MIT © Brian X Base Team