validate-functional-graph

You validate a functional graph by running automated checks against source documents to detect empty nodes, duplicates, citation coverage gaps, and persona overlaps, ensuring traceability. This process generates structured reports with severity levels and prioritized fix recommendations.

Empty nodes and uncited scenarios in your functional graph occur when validation against source documents is skipped. Running an automated quality check detects these gaps, verifies citation traceability, and flags missing descriptions to prevent downstream development errors.

The best way to audit requirement tracing and persona health is to validate the functional graph for cross-persona overlaps, platform-agnostic compliance, and citation traceability. This generates a structured report with P0-P2 severity levels and prioritized fixes without manual auditing.

Yes, you can check your functional graph for platform-agnostic compliance by validating descriptions against source documents. The validation process automatically flags UI-specific language, detects cross-persona overlaps, and outputs a structured report with severity levels and fix recommendations.

Yes, functional graph validation works without manual auditing by automatically checking source coverage, citations, and description completeness for impact analysis. It applies to software engineering workflows to maintain graph integrity and outputs structured reports with prioritized recommendations.

Automated functional graph quality checks are limited to validating against available source documents. If source documents are missing or incomplete, the validation cannot verify citation traceability or source coverage, meaning the automated report will only reflect the gaps present in the provided inputs.