docs:update-docs

Automating documentation updates requires analyzing code changes and generating prioritized tasks for READMEs, docs/, and JSDoc. A multi-agent workflow coordinates parallel analysis, automated discovery, and iterative tech-writer reviews to keep documentation in sync with local modifications.

A multi-agent workflow for documentation uses parallel haiku agents to analyze repository changes and plan updates. Tech-writer agents then generate module READMEs, update API references, and review outputs iteratively to enforce project conventions and minimize documentation bloat.

Finding outdated documentation involves automated discovery across the repository to identify gaps impacting READMEs, docs/, JSDoc, and API references. It analyzes the documentation structure and generates prioritized tasks to update indices and references based on recent code changes.

Yes, automated documentation generation works with JSDoc and API references by analyzing the existing documentation structure. It identifies changes impacting these files, generates updates for module READMEs, and updates navigation indices while enforcing project conventions through iterative reviews.

The best way to update docs navigation indices is using an automated workflow that analyzes documentation structure and identifies impacted files. It generates prioritized tasks for index updates and validates them through iterative tech-writer agent reviews to ensure alignment with project conventions.

You should avoid using automated multi-agent documentation workflows when manual review is preferred over iterative tech-writer agents, or when repository conventions are not yet established. It is designed for structured projects needing parallel analysis and automated updates across docs/, READMEs, and JSDoc.