Analytics Documentation Generator
Generate production-grade analytics documentation in minutes
What You Can Do
You can create comprehensive documentation for your data platforms, metrics, and analytics infrastructure that stakeholders actually understand. The skill generates clear data dictionaries, metric definitions, pipeline diagrams, and runbooks that bridge the gap between technical teams and business users. Your documentation stays consistent with your actual infrastructure while being instantly accessible to analysts, managers, and engineers.
Features
Automatically catalog all tables, columns, data types, freshness guarantees, and ownership
Define business metrics with calculation logic, expected values, SLAs, and common use cases
Generate architecture diagrams, data lineage, and ETL/ELT workflow explanations
Write plain-English summaries that translate technical concepts for business audiences
Auto-generate reusable SQL and dbt snippets with realistic examples for each table
Create troubleshooting guides with diagnostic queries and incident recovery procedures
Document data sources, transformations, downstream consumers, and dependencies
Establish PII classifications, access policies, and data quality requirements
Example Output
Metric Definition Card
Metric: Customer Lifetime Value (CLV)
Business Definition: Total expected revenue from a customer across their entire relationship
Owner: Revenue Analytics team (analytics@company.com)
SLA: Updated daily, 99.5% accuracy
Calculation: SUM(order_total) WHERE customer_id = X AND status = 'completed'
Common Uses: Segmentation, churn prediction, acquisition ROI
Limitation: Excludes refunds and chargebacks
Data Dictionary Excerpt
Table: events_raw
Purpose: Raw clickstream events from web and mobile applications
Freshness: Updated every 5 minutes
Ownership: Data Platform team
Columns:
- event_id (UUID): Unique identifier for each event
- user_id (VARCHAR): Customer identifier, NULL for anonymous users
- event_timestamp (TIMESTAMP): UTC time event occurred
- event_type (VARCHAR): category, purchase, login, etc.
Runbook Snippet
### Pipeline Failed: customer_daily_aggregation
**Error:** "Connection timeout after 900s"
**Root Cause:** Source database maintenance window not communicated
**Recovery:**
1. Check source system status: SELECT * FROM status_dashboard
2. If available, restart pipeline via dbt run -s customer_daily_aggregation
3. Verify completeness: SELECT COUNT(*) FROM customer_daily
What's Included
- SKILL.md: Full analytics documentation generator prompt with examples
- Templates: Data dictionary, metric card, runbook, and lineage diagram templates
- Checklists: Schema change reviews, quarterly documentation audits, access policy updates
- Workflows: Collaboration workflows with data teams, documentation PR review process, escalation procedures
- Examples: Sample documentation for real-world tables, metrics, and pipelines
- Guidelines: Best practices for metric definitions, naming conventions, and governance structures
Who It's For
- Data Engineers — Building and maintaining data platforms and pipelines
- Analytics Engineers — Documenting dbt models, metrics, and transformation logic
- Data Analysts — Explaining datasets and metric calculations to business stakeholders
- Data Governance Teams — Establishing PII policies, access controls, and data quality standards
- Platform Product Managers — Onboarding teams and documenting infrastructure changes
Best For
- Documenting new data sources, tables, and major schema changes
- Creating metric definitions with business context and calculation logic
- Building runbooks for common data pipeline failures and troubleshooting
- Establishing data governance frameworks and access policies
- Onboarding new team members to your analytics infrastructure
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