What problem does it solve? Finding relevant passages across large collections of PDFs, Markdown, and text files requires more than keyword matching. This Skill guides the use of cementic, a local semantic search CLI that watches directories, extracts and embeds documents into Postgres (pgvector + vectorscale), and serves versioned semantic search. ## Core Features & Use Cases - Directory indexing and watching: Run cementic start to extract, chunk, and embed documents into versioned pipeline revisions while old revisions stay searchable. - Semantic search and collection management: Query active revisions with cementic search, and promote, reindex, or remove collections and revisions. - Pipeline debugging and diagnostics: Use cementic doctor for readiness checks and pipe extract | chunk | embed together to inspect the pipeline without a database. - Use Case: Point cementic at a folder of research papers, wait for indexing to finish, then run cementic search "transformer inference" to retrieve semantically relevant passages across the whole library. ## Quick Start Ask the assistant to check cementic readiness with doctor, start Postgres if needed, then index a chosen directory into a named collection and run a semantic search query against it.