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Documentation drift is detected by scanning for stale content using objective signals like linting and CI checks to find mismatches between docs and real code behavior. This process identifies obsolete documentation, dead links, and high-churn areas.

Automated documentation maintenance runs recurring drift signals to queue fix-up work, consolidating findings into actionable specifications and plans. It targets code alignment, runbook accuracy, and generated context freshness to keep docs reliable.

You generate fix-up tasks by running objective drift signals that consolidate documentation inconsistencies into actionable specifications and plans. This creates prioritized, small, and independently shippable changes for doc-fix initiatives.

Yes, documentation drift detection operates without external dependencies, relying on built-in scripts and references. It scans your repository to identify obsolete documentation and high-churn areas using objective signals like linting checks.

You need to scan for stale documentation and dead links after code updates or feature releases to ensure docs match current software behavior. Running drift detection identifies obsolete content and generates plans to update it.

Runbook accuracy degrades because frequent code updates cause documentation drift, leaving runbooks misaligned with actual code behavior. Stale content identification scans for these high-churn areas to flag obsolete documentation for updates.