LLM Status vs Retrace

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

Record, replay, fork & share AI agent executions. See every LLM call, tool call, and error your agent makes, then debug in seconds. Free for 1,000 traces/mo.

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.

About Retrace

Record, replay, fork & share AI agent executions. See every LLM call, tool call, and error your agent makes, then debug in seconds. Free for 1,000 traces/mo. Retrace records every model and tool call your agent makes, so you can re-run a failure, branch from the exact step it went wrong, and check your fix before you ship. This is the reliability loop Retrace owns, end to end. Now a production failure becomes a permanent regression test you can re-run.