claims-validator

Documentation claims validation automatically scans for unsupported metrics, unverified statistics, and unsubstantiated statements. It flags performance percentages without benchmarks, time estimates without methodology, and feature descriptions for unimplemented capabilities, then returns a structured report with remediation recommendations.

Claims validation detects performance metrics lacking data, time or cost estimates without basis, marketing superlatives presented as facts, comparative claims without evidence, and features described as implemented that don't exist in the codebase. It traces each flagged claim to its source line.

Yes, claims validation scans documentation for unsupported metrics and unverifiable statements across sources and codebases. It identifies citation validity issues and cross-references feature assertions against actual implementation, returning traceable evidence sources for each claim.

Automated claims validation eliminates manual review overhead by systematically identifying misleading metrics, made-up statistics, and unverifiable statements at scale. It reduces human error and catches inconsistencies between documented claims and actual codebase capabilities.

The validation report details each unsupported claim by type—metrics, time estimates, feature assertions—with line numbers, evidence of why claims lack support, and recommended remediations. Results are structured for actionable documentation fixes and compliance tracking.