Agent run tracing
Shows each agent run as one trace, with model and tool calls represented as spans containing duration, token usage, cost, and error information.
Loading page…
Coding / product dossier
Trace AI agent runs, compare prompt evaluations, and monitor errors, token costs, and agent loops.
Product brief
telemetry.dev shows each run of your AI agent as one trace. Each model call and tool call is a span with its duration, tokens, cost, and error. Prompts and evals use the same traces: change a prompt without a deploy, then run it on a dataset and compare the scores with production. Alerts tell you about errors, cost spikes, and agent loops. Connect with our TypeScript or Python SDK, or with the OpenTelemetry exporter that you already use.
Why we selected it
A substantive agent-operations toolkit combining traces, prompt management, evaluations, and alerts. Python, TypeScript, and OpenTelemetry integration make adoption concrete. Cost-spike monitoring is particularly timely,
Product preview saved with our daily selection
Capability scan
Only capabilities supported by the product information we collected are listed here.
Shows each agent run as one trace, with model and tool calls represented as spans containing duration, token usage, cost, and error information.
Allows prompt changes without a deployment, using the same traces as agent monitoring and evaluations.
Runs prompts against a dataset and compares evaluation scores with production.
Alerts on errors, cost spikes, and agent loops.
Connects through TypeScript or Python SDKs, or an existing OpenTelemetry exporter.
Best-fit use cases
FAQ
Each run appears as one trace. Model and tool calls appear as spans with duration, tokens, cost, and error information.
Yes. telemetry.dev supports changing a prompt without a deploy, then running it on a dataset and comparing scores with production.
It supports TypeScript and Python SDKs, as well as an existing OpenTelemetry exporter.
Alerts cover errors, cost spikes, and agent loops.