Add database table schemas documentation for LLM agents

Overview

To help LLM agents (like Claude Code) better understand and work with the nf-core stats data, we should document the database table schemas in a machine-readable format.

Current situation

• LLM agents working with this project need to understand the data structure
• Evidence.dev pages reference tables like github_traffic_stats, github_contributor_stats, etc.
• SQL queries in sources/nfcore_db/ and queries/ directories reference various table schemas
• No centralized schema documentation exists for automated tools

Proposed solution

Create comprehensive table schema documentation that includes:

1. Schema documentation file

• Create docs/database-schemas.md or similar
• Document all main tables with column descriptions, types, and sample data
• Include relationships between tables
• Add notes about data collection frequency and sources

2. Key tables to document

From the existing SQL queries and pipeline code, prioritize:

• github_traffic_stats (repository views/clones)
• github_contributor_stats (contributor activity by week)
• github_issue_stats (issues and pull requests)
• nfcore_pipelines (repository metadata)
• slack_messages (Slack channel activity)
• slack_members (Slack membership stats)
• org_members (GitHub organization members)

3. Machine-readable format considerations

• Use consistent markdown tables
• Include JSON schema definitions if helpful
• Consider adding dlt schema exports
• Make it easy for LLMs to parse and understand

Benefits

• LLM agents can write better SQL queries
• Faster development when creating new visualizations
• Better understanding of available data for new features
• Improved onboarding for developers
• Self-documenting codebase

Acceptance criteria

• Create schema documentation covering all major tables
• Include column names, types, descriptions, and sample values
• Document table relationships and foreign keys
• Add data collection notes (frequency, source APIs)
• Update CLAUDE.md to reference the schema documentation
• Ensure documentation is easily discoverable and maintainable

This will significantly improve the ability of Claude Code and other LLM agents to understand and work with the nf-core stats data effectively.

Start by reviewing the SQL queries in sources/nfcore_db/ and queries/, then inspect the pipeline code and Evidence.dev pages that reference the listed tables. Use those sources to define the schemas, relationships, sample values, and collection notes in docs/database-schemas.md or a similar file. Update CLAUDE.md to link to the documentation and verify that all acceptance criteria are covered.