collector-hand-skill

OSINT intelligence collection is automated by extracting entities and relationships across open sources to construct a structured knowledge graph. This replaces manual gathering with auditable, repeatable workflows for continuous target monitoring.

Change detection works by continuously mapping extracted entities and relationships to identify notable shifts in targets like companies, people, or markets. It surfaces risks and sentiment changes, producing alerts for auditable reporting.

Yes, you can use this OSINT skill for market and business intelligence across domains like tech and people. It extracts entities from open sources and applies sentiment analysis to surface notable shifts and risks for your specified targets.

The best way to start an OSINT collection cycle is to specify a target_subject along with your chosen focus_area and collection_depth. This initiates automated entity extraction, knowledge-graph construction, and source attribution across open sources.

Automated sentiment analysis surfaces notable shifts and risks by continuously monitoring extracted entities across open sources. It generates structured alerts that enable auditable reporting for your target monitoring workflows.

The OSINT entity extraction process produces structured outputs including mapped entities, relationships, and alerts. These outputs enable change detection, sentiment analysis, and source attribution for auditable intelligence reporting.