cross-document-verification

Cross-document verification enforces compliance by comparing anchored facts across multiple documents within a case. It extracts anchors, locates target documents, applies consistency checks, and returns a case-level verdict with evidence and severity.

To verify income proof against bank statements for a loan application, you define a cross-document path: start document type, anchor entity, target document type, and consistency rules. The check.py workflow then traverses the case to execute the validation.

Yes, you can check reference integrity between main contracts and attachments. The skill supports case-level rule orchestration, allowing you to define explicit anchors and cross-document paths to validate consistency across bundled legal files.

Cross-document verification separates the builder from the runtime executor. It defines and guides the creation of rules with explicit anchors and PASS/FAIL criteria, enabling safe, auditable production workflows to be executed later by a workflow engine.

The best way to define cross-document consistency rules for multi-source bundles is using the rule-builder. You specify the start document type, anchor entity, target document type, target entity, and consistency rules to establish executable PASS/FAIL criteria.

A limitation is that cross-document verification requires explicit anchors and defined cross-document paths for every rule. Without extracted entities and properly structured start-to-target document mappings, the case-level workflow traversal cannot return a valid verdict.