validation-quarantine

Development

Data validation with quality scoring and quarantine for suspicious records. Validates incoming data without blocking the pipeline, enabling manual review of edge cases.

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Data Validation & Quarantine

Validate incoming data with quality scoring and quarantine suspicious records without blocking the pipeline.

When to Use This Skill

Processing external data sources that are unreliable
Need quality scoring beyond simple schema validation
Want to quarantine suspicious data for manual review
Can't afford to block the pipeline for bad data

Core Concepts

External data sources are unreliable. Schema violations crash pipelines, low-quality data pollutes databases, and you can't manually review every record.

The solution:

Validate against schema
Score quality based on domain rules
Pass high-quality data through
Quarantine suspicious data for review
Reject invalid data

┌─────────────┐     ┌───────────────┐     ┌─────────────┐
│  Raw Data   │────▶│   Validator   │────▶│   Valid     │
└─────────────┘     └───────────────┘     └─────────────┘
                           │
                           ▼
                    ┌─────────────┐
                    │ Quarantine  │
                    └─────────────┘

Implementation

TypeScript

import { z, ZodError } from 'zod';

interface ValidationResult<T> {
  success: boolean;
  data?: T;
  errors?: { path: string; message: string; code: string }[];
  qualityScore: number;
  warnings: string[];
}

interface BatchResult<T> {
  valid: T[];
  invalid: { original: unknown; errors: any[] }[];
  quarantined: { original: unknown; score: number; warnings: string[] }[];
  metrics: {
    totalProcessed: number;
    validPercent: number;
    avgQualityScore: number;
    processingTimeMs: number;
  };
}

class DataValidator<T> {
  constructor(
    private schema: z.ZodSchema<T>,
    private qualityScorer: (data: T) => { score: number; warnings: string[] },
    private quarantineThreshold = 50
  ) {}

  validate(raw: unknown): ValidationResult<T> {
    try {
      const parsed = this.schema.parse(raw);
      const { score, warnings } = this.qualityScorer(parsed);
      return { success: true, data: parsed, qualityScore: score, warnings };
    } catch (error) {
      if (error instanceof ZodError) {
        return {
          success: false,
          errors: error.errors.map(e => ({
            path: e.path.join('.'),
            message: e.message,
            code: e.code,
          })),
          qualityScore: 0,
          warnings: [],
        };
      }
      throw error;
    }
  }

  validateBatch(items: unknown[]): BatchResult<T> {
    const start = Date.now();
    const valid: T[] = [];
    const invalid: any[] = [];
    const quarantined: any[] = [];
    let totalScore = 0;

    for (const item of items) {
      const result = this.validate(item);
      
      if (!result.success) {
        invalid.push({ original: item, errors: result.errors });
      } else if (result.qualityScore < this.quarantineThreshold) {
        quarantined.push({
          original: item,
          score: result.qualityScore,
          warnings: result.warnings,
        });
      } else {
        valid.push(result.data!);
        totalScore += result.qualityScore;
      }
    }

    return {
      valid,
      invalid,
      quarantined,
      metrics: {
        totalProcessed: items.length,
        validPercent: items.length > 0 ? (valid.length / items.length) * 100 : 0,
        avgQualityScore: valid.length > 0 ? totalScore / valid.length : 0,
        processingTimeMs: Date.now() - start,
      },
    };
  }
}

// ============================================
// Quality Scorer Example
// ============================================

interface Article {
  title: string;
  url: string;
  domain: string;
  publishedAt: string;
}

function scoreArticle(article: Article): { score: number; warnings: string[] } {
  let score = 100;
  const warnings: string[] = [];

  // Title checks
  if (article.title.length < 20) {
    score -= 10;
    warnings.push('Short title');
  }
  if (/\b(click|subscribe|newsletter)\b/i.test(article.title)) {
    score -= 15;
    warnings.push('Promotional language');
  }

  // Source checks
  const ugcPlatforms = ['blogspot', 'wordpress', 'medium'];
  if (ugcPlatforms.some(p => article.domain.includes(p))) {
    score -= 10;
    warnings.push('User-generated content platform');
  }

  // Freshness check
  const ageMs = Date.now() - new Date(article.publishedAt).getTime();
  if (ageMs > 365 * 24 * 60 * 60 * 1000) {
    score -= 20;
    warnings.push('Article over 1 year old');
  }

  return { score: Math.max(0, score), warnings };
}

// ============================================
// Quarantine Store
// ============================================

type QuarantineReason = 
  | 'low_quality_score'
  | 'suspicious_content'
  | 'duplicate_detected'
  | 'source_blacklisted';

interface QuarantinedItem<T> {
  id: string;
  data: T;
  reason: QuarantineReason;
  qualityScore: number;
  warnings: string[];
  quarantinedAt: string;
  reviewStatus: 'pending' | 'approved' | 'rejected';
}

class QuarantineStore<T> {
  private items = new Map<string, QuarantinedItem<T>>();
  private maxItems = 10000;
  private autoRejectDays = 7;

  add(
    data: T, 
    reason: QuarantineReason, 
    score: number, 
    warnings: string[]
  ): string {
    const id = `q_${Date.now()}_${Math.random().toString(36).slice(2, 8)}`;
    
    this.items.set(id, {
      id,
      data,
      reason,
      qualityScore: score,
      warnings,
      quarantinedAt: new Date().toISOString(),
      reviewStatus: 'pending',
    });

    this.enforceLimit();
    return id;
  }

  approve(id: string): T | null {
    const item = this.items.get(id);
    if (!item || item.reviewStatus !== 'pending') return null;
    
    item.reviewStatus = 'approved';
    return item.data;
  }

  reject(id: string): boolean {
    const item = this.items.get(id);
    if (!item) return false;
    
    item.reviewStatus = 'rejected';
    return true;
  }

  getPending(limit = 100): QuarantinedItem<T>[] {
    return Array.from(this.items.values())
      .filter(i => i.reviewStatus === 'pending')
      .slice(0, limit);
  }

  releaseApproved(): T[] {
    const approved: T[] = [];
    for (const [id, item] of this.items) {
      if (item.reviewStatus === 'approved') {
        approved.push(item.data);
        this.items.delete(id);
      }
    }
    return approved;
  }

  autoRejectStale(): number {
    const cutoff = Date.now() - this.autoRejectDays * 24 * 60 * 60 * 1000;
    let count = 0;
    
    for (const item of this.items.values()) {
      if (item.reviewStatus === 'pending' && 
          new Date(item.quarantinedAt).getTime() < cutoff) {
        item.reviewStatus = 'rejected';
        count++;
      }
    }
    return count;
  }

  private enforceLimit(): void {
    if (this.items.size <= this.maxItems) return;
    
    const sorted = Array.from(this.items.entries())
      .sort((a, b) => {
        if (a[1].reviewStatus === 'rejected' && b[1].reviewStatus !== 'rejected') return -1;
        return new Date(a[1].quarantinedAt).getTime() - new Date(b[1].quarantinedAt).getTime();
      });

    while (sorted.length > this.maxItems) {
      const [id] = sorted.shift()!;
      this.items.delete(id);
    }
  }
}

Usage Examples

Basic Validation Pipeline

const ArticleSchema = z.object({
  title: z.string().min(1),
  url: z.string().url(),
  domain: z.string(),
  publishedAt: z.string().datetime(),
});

type Article = z.infer<typeof ArticleSchema>;

const validator = new DataValidator(ArticleSchema, scoreArticle, 50);
const quarantine = new QuarantineStore<Article>();

// Process batch
const result = validator.validateBatch(rawArticles);

// Handle quarantined items
for (const q of result.quarantined) {
  quarantine.add(q.original as Article, 'low_quality_score', q.score, q.warnings);
}

// Use valid data
await saveToDatabase(result.valid);

console.log(`Processed: ${result.metrics.totalProcessed}`);
console.log(`Valid: ${result.valid.length} (${result.metrics.validPercent.toFixed(1)}%)`);
console.log(`Quarantined: ${result.quarantined.length}`);

Best Practices

Never block the pipeline for bad data - quarantine instead
Quality scores are domain-specific - tune thresholds based on your data
Auto-reject stale quarantined items - don't let the queue grow forever
Expose quarantine for manual review via admin UI
Track metrics to identify data quality trends

Common Mistakes

Blocking the entire pipeline when validation fails
Using only schema validation without quality scoring
Not setting limits on quarantine store size
Forgetting to auto-reject stale items
Not exposing quarantine for manual review

Related Patterns

batch-processing - Process validated items efficiently
deduplication - Deduplicate before validation
error-sanitization - Sanitize validation error messages