What problem does it solve? Knowledge spread across multiple domains often hides genuine structural parallels that manual review misses. This Skill systematically scans a knowledge workspace to surface cross-domain bridge candidates so curators can connect related ideas instead of leaving them siloed. ## Core Features & Use Cases - Three-Level Detection: Finds structural bridges in connections.json, category overlaps across domains, and content-level similarity via cross_domain_links in domains.yaml. - Candidate Assessment: Evaluates each candidate for genuine parallel, relation type, strength, and novelty before proposing it. - Machine-Readable Output: Persists the full candidate set to log/bridge-candidates.json as a regenerable derived artifact, then applies confirmed bridges to connections.json with event logging. - Use Case: During a curation cycle, run bridge detection to discover that a cosmology card on observer effects parallels a philosophy-of-mind card on self-model observer loops, then confirm and record the new connection. ## Quick Start Ask the agent to find connections across domains in the current workspace and review the proposed bridge candidates.