detectkit

Interactively tune a detectkit metric's detector in the browser cockpit: stand up a sandbox config, open `dtk tune`, and guide the user to turn the detector's knobs on their real series and watch the confidence band recompute live — **with the autotune engine built in** (an Autotune mode that searches server-side and re-seeds the knobs), plus Label/Review to mark or confirm incidents — then write the chosen config back into the metric YAML. Use when the user wants to tune a detector by hand / interactively / in the browser, see and adjust the band or alerts live, set up a tuning sandbox to "turn the knobs" themselves, reduce false alerts hands-on, or visually mark/confirm incidents. This is the primary, hands-on entry point for dialing in a metric; it contains autotune, so prefer it whenever the user wants to be in the loop.

Configure a detectkit project's database connection (and optionally a first alert channel) in profiles.yml so `dtk run` works end to end. Use for first-time setup, right after `dtk init`, when the user asks to connect detectkit to their database or set up profiles.yml, or when a run fails with "internal_database must be set", "data_database must be set", "profiles.yml not found", or "Connection refused". Interactive and database-type-aware.

Scaffold a new detectkit metric as a validated YAML file under metrics/. Use when the user wants to add or create a detectkit metric, monitor a new query or table, or set up anomaly detection / alerting on a time series. Produces a metrics/<name>.yml that passes config validation and is ready to run with dtk.

Automatically tune and optimize a detectkit metric's anomaly detector: pick the best detector type and hyperparameters, auto-configure seasonality, and build a working alert from a monitoring request and tune it on real data. Use when the user wants to tune/optimize a metric's detector, pick the best anomaly detector, reduce false positives/negatives by tuning, choose detector parameters automatically, or stand up an alert from scratch and tune it. Gathers extra seasonality and incident history, writes a labels file, runs `dtk autotune`, then explains the chosen config and shows how it behaves against the database. Produces a tuned, annotated metric YAML ready to run.

Report a detectkit bug, request a feature, or send feedback to the maintainers as a GitHub issue on the upstream repo (alexeiveselov92/detectkit). Use when a dtk command errors or behaves unexpectedly and it looks like a detectkit defect (not the user's config), when the user wishes detectkit did something it doesn't, or when they ask to report/file an issue, send feedback, or contact the maintainers. Auto-collects diagnostic context, redacts all secrets, and never submits without explicit confirmation.