photoscrawl is a macOS CLI tool that crawls, archives, and analyzes Apple Photos libraries. It extracts metadata, faces, search indexes, and performs classification using local multimodal models (Ollama/OpenAI). The tool stores observations and evidence in a local SQLite database (photos.sqlite) rather than final truth, enabling later hypothesis generation for people, trips, and places. It provides subcommands for crawling, importing, classifying, searching, ranking, similarity, place backfill, and evaluation card generation. Architecture: The system is a Go CLI with a modular internal structure. It uses a crawlkit shared library for crawler mechanics, control, output, and store. The Apple Photos library is accessed via PhotoKit (cgo/Objective-C bridges) and direct SQLite snapshots. Data flows: snapshot Apple Photos database -> import metadata, faces, search indexes -> classify assets (metadata observations, then optional local model inference) -> store evidence in archive. Place backfill uses a subprocess bridge for reverse geocoding with rate limiting. Eval cards prepare images and run Ollama models for evaluation. Key entry points: cmd/photoscrawl/main.go (CLI), internal/archive/crawl.go (crawl logic), internal/archive/classify.go (classification queue), internal/place/backfill.go (batch geocoding), internal/evalcard/evalcard.go (model evaluation). External dependencies: Apple Photos (macOS), SQLite, Ollama/OpenAI (optional), crawlkit, Go standard library. The codebase demonstrates strong engineering practices with comprehensive tests, CI/CD, vulnerability scanning, and schema migrations. It is actively maintained with frequent dependency updates and a focus on privacy (all model calls local by default, no private data in repo).