Drupal AI Content Impact Analyzer
Drupal AI Content Impact Analyzer is a module that uses AI to evaluate how content changes ripple through a Drupal site before they go live. It inspects entity references, views dependencies, menu links, and block placements to surface which pages, layouts, and downstream content will be affected when you edit, unpublish, or delete a node. Instead of discovering broken references after the fact, editors get a clear impact report at authoring time.
Large Drupal sites accumulate dense webs of content relationships. A single node might feed into multiple views, appear as a referenced teaser on landing pages, and anchor a menu subtree. Removing or restructuring it without understanding those connections creates silent breakage that only surfaces when a visitor hits a 404 or an empty listing. I built this analyzer to close that feedback gap by combining Drupal's entity API with an LLM layer that scores the severity of each downstream effect and suggests mitigation steps. View Code
Technical takeaway: the key design choice is separating the structural graph walk from the AI scoring pass. The first phase is pure Drupal — querying entity reference fields, views configurations, and menu link content plugins to build a dependency graph. The second phase sends that graph, not raw content, to the LLM for impact classification. This keeps token usage low, makes the structural analysis deterministic and testable, and lets the AI focus on the judgment call: how critical is this dependency, and what should the editor do about it.