CIA Data Integration Skill

🔴 AI FIRST Quality Principle

Apply the AI FIRST principle: never accept first-pass quality. Minimum 2 iterations. Read all output, improve every section. No shortcuts.

Purpose

This skill provides expertise in consuming JSON exports from the CIA (Citizen Intelligence Agency) platform, implementing robust caching strategies, and ensuring data quality through schema validation.

Core Principles

1. CIA is Source of Truth - Never modify CIA's pre-computed data
2. Validate Before Cache - Always validate against CIA-provided JSON schemas
3. Version Tracking - Track all CIA data updates with timestamps
4. Graceful Degradation - Fall back to cached data if CIA unavailable
5. Data Freshness - Monitor and alert on stale data (> 24 hours)
6. Audit Logging - Log all data operations for traceability

Enforces

CIA Export Consumption

• Fetch 19 visualization products from CIA platform
• Handle rate limiting and connection failures
• Implement retry logic with exponential backoff
• Circuit breaker pattern for API failures

JSON Schema Validation

// Validate CIA export against schema
import Ajv from 'ajv';

const ajv = new Ajv({ allErrors: true });
const schema = await fetchCIASchema(productName);
const validate = ajv.compile(schema);

if (!validate(data)) {
  throw new ValidationError(validate.errors);
}

Caching Strategy

data/cia-exports/
  current/          # Latest CIA exports (19 files)
  archive/          # Historical versions (date-stamped)
  metadata/         # Fetch timestamps, validation status

Data Freshness Monitoring

• Track last fetch timestamp
• Alert if data > 24 hours old
• Display staleness warnings to users
• Automatic fallback to cached data

When to Use

• Implementing CIA export fetch workflows
• Validating CIA JSON data
• Designing caching strategies
• Building data consumption pipelines
• Monitoring data freshness
• Handling API failures gracefully

Examples

CIA Export Client

class CIAExportClient {
  async fetchExport(productName) {
    const url = `https://www.hack23.com/cia/api/export/${productName}.json`;
    const data = await fetch(url, { timeout: 30000 });
    
    await this.validateSchema(productName, data);
    await this.cacheWithVersion(productName, data);
    
    return data;
  }
}

Automated Workflow

# .github/workflows/fetch-cia-exports.yml
name: Fetch CIA Exports
on:
  schedule:
    - cron: '0 2 * * *'  # 02:00 CET daily

jobs:
  fetch:
    steps:
      - name: Fetch CIA exports
        run: node scripts/fetch-cia-exports.js
      
      - name: Validate schemas
        run: node scripts/validate-cia-data.js
      
      - name: Commit if changed
        run: |
          if git diff --quiet data/cia-exports/; then
            echo "No changes"
          else
            git add data/cia-exports/
            git commit -m "Update CIA exports"
            git push
          fi

Remember

• CIA maintains the digital twin - riksdagsmonitor consumes it
• Validate all data before caching
• Monitor freshness and alert on staleness
• Provide graceful fallback to cached data
• Never modify CIA's pre-computed intelligence
• Log all operations for audit trail
• Respect rate limits and implement backoff

References

• CIA Platform
• CIA Export Specs
• JSON Schema Validation
• Hack23 Secure Development Policy

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Version: 1.0
Last Updated: 2026-02-06
Category: Data Integration
Maintained by: Hack23 AB

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🔗 Integration with agentic workflows & analysis artifacts

This skill is consumed by the 11 agentic news workflows in .github/workflows/news-*.md. The authoritative contract lives in .github/prompts/README.md; this skill supplies domain expertise on top of that contract.

• Analysis product → ai-driven-analysis-guide.md + every template in analysis/templates/.
• Required before any article: 9 core artifacts (14 for Tier-C) in analysis/daily/$ARTICLE_DATE/$SUBFOLDER/; 05-analysis-gate.md is the single blocking gate.
• gh-aw v0.69.3 docs: abridged · complete · blog series.