argot vs LLM Status

argot, find code your repository would question Skip to main content.

Track where every AI model is used across your apps, and get warned before one is deprecated or retired.

About argot

argot, find code your repository would question Skip to main content. Clean, type-correct PRs can still be foreign to your repository. Valid Python, but a framework this repo has never imported. 154/164 (93.9%), detector-specific fixture catch; controls and accepted-history results are separate. A finding is a prompt for human judgment, not proof of a defect. Then run argot init and choose a recurring check path. Fixture recall; the changed symbol is visible in the diff.

About LLM Status

Track where every AI model is used across your apps, and get warned before one is deprecated or retired. Run mm for the full terminal dashboard: it scans the current repo on launch, then you arrow through every model it calls, browse the registry, and see what's new, live. Both pull the signed registry from cdn.llmstatus.ai once, then run offline. The Here and What's New tabs read straight off the signed registry, no account, works offline.