Signal Correlator Skill

Technology signal correlation cross-validates detection data from multiple domains to confirm likely technologies and flag contradictory evidence. It groups raw signals by technology, computes agreement scores, and surfaces version or framework mismatches for review.

Cross-source agreement scoring evaluates how consistently multiple signals like HTTP, DNS, and JavaScript evidence corroborate the same technology. It groups raw signals by technology and computes agreement patterns to distinguish high, medium, and low-quality inferences.

Contradictory evidence occurs when different detection domains yield mutually exclusive signals, version mismatches, or temporal inconsistencies. Conflict detection groups these signals to highlight disagreements so findings can be reviewed instead of silently overwritten during inference.

Inference quality scoring assesses inferred technologies by evaluating evidence diversity and strength across collection domains. It distinguishes high, medium, and low-quality inferences to guide follow-up validation for technology stack identification.

Yes, signal correlation supports cross-validating HTTP, DNS, TLS, JavaScript, HTML, repository, job postings, and archive signals. It groups these diverse sources by technology to compute agreement scores and detect framework conflicts.

Running a correlate operation with raw signals and inferred technologies produces correlated technologies, conflicts, and an overall quality assessment in a single JSON result. This unifies evidence to confirm technologies and detect version mismatches.