numbat brings unified endpoint visibility for AI agents across desktop apps, CLIs, IDEs and gateways. It hooks into supported agents via local plugins and OTLP/HTTP log exporters, then normalizes live and at-rest activity into a single event model. A built-in Common Expression Language (CEL) engine runs detection locally; you can write results to stdout, a file or push them over HTTP. Blocking is off by default and works only with specific synchronous pre-action hooks—enforcement requires marking rules with enforce: true and installing numbat in enforce mode. Under the hood, numbat ships with multi-step sequence rules, custom YAML rules and JSON Schema–defined NDJSON output for events, findings, enforcement decisions, indicators and scan summaries. It can reconstruct forensics from on-disk session artifacts even if numbat wasn’t installed beforehand. You’ll get read-only commands—agents, scan, timeline—to map what’s present and timeline multi-step actions. Hooks live-capture only start in monitor-only mode; to turn on blocking you copy a shipped rule into your policy directory, set enforce: true, bump the version and run numbat hook install with --enforce. The single-binary works on macOS, Linux and Windows (amd64, arm64) and builds without cgo. Download releases with SHA-256 checksums or install via go install …/numbat@latest. For custom builds: CGO_ENABLED=0 go build -trimpath -o numbat ./cmd/numbat. Once installed, commands include hook install/status/uninstall, scan, collect, ship for record delivery, plus rules check/list/test for policy work, and case build/verify for portable investigation bundles. Everything pivots around live-capture hooks, local CEL evaluation and NDJSON records you can ship or bundle.