Documentation Automation Model
Summary
Automation detects change, proposes affected documentation, maintains machine-readable relationships, and generates reviewable drafts. It does not approve, publish, or disclose content autonomously.
Audience
- Documentation tooling, engineering productivity, QA, DevOps, architecture, and security teams
Reference Content
Automation capabilities
- Documentation impact analysis: map changed source artifacts to documented nodes and traverse
used_byrelationships. - Affected-page detection: rank pages by direct source, service, API, event, database, UI, and dependency relationships.
- Automatic draft generation: create evidence-linked drafts with
documentation_status: draftonly. - Dependency graph updates: propose new, changed, or removed edges and require owner review for semantic changes.
- Future GitHub automation: comment on pull requests, create documentation tasks, and run quality gates without auto-merging or publishing.
- Future MCP integration: expose authorized source and documentation graph context with visibility-aware access controls.
- Future OpenAPI generation: generate API reference from approved specifications and retain generator/version provenance.
- Future event catalog: generate contract reference from versioned event definitions and verified producer/consumer inventories.
Controls
- Preserve visibility and ownership metadata.
- Never include secrets, personal data, restricted source, or inaccessible graph metadata in lower-visibility outputs.
- Record source revision, generator, time, and affected nodes.
- Treat deletion and deprecation as review-requiring changes.
- Require all existing validation and build gates before review.
- Never auto-approve, auto-publish, commit, deploy, or notify external audiences without explicit authorization.
Related Articles
See Also
Keywords
- Impact analysis
- Documentation generation
- Graph automation
Revision Information
- Status: Draft
- Last reviewed: 2026-07-15
- Review cycle: Quarterly