Understand what your AI application did, find what went wrong, and measure improvements.
Datool brings traces, datasets, scorers, and evaluation runs into one project. Start with a trace from your application, inspect its inputs and outputs, then turn useful examples into repeatable tests.
Send your first trace — Choose AI SDK, TypeScript, Python, or LangGraph. The Python function and graph examples need no model API key.
Run your first evaluation — Connect an app, catch a failing case, fix it, and compare saved runs. No model key is required.
Use your first managed prompt — Publish a template and fetch the latest published version from your application.
Understand the concepts — Learn how traces, spans, sessions, datasets, and scores fit together.
Connect your existing instrumentation — Export OpenTelemetry spans and instrument AI SDK calls.
Use the Playground to try individual inputs, Prompts to version message templates, and Dashboards to follow changes over time.
These docs are public. Your project's data and API operations require authentication.
Every documentation page supports Accept: text/markdown or a .md suffix. For example, with DATOOL_BASE_URL set to your instance's origin:
curl -H 'Accept: text/markdown' "$DATOOL_BASE_URL/docs/evaluation/datasets"
curl "$DATOOL_BASE_URL/docs/evaluation/datasets.md"Both return the same Markdown with Content-Type: text/markdown. Use /docs.md for this documentation index. The View as Markdown link on each page also works, and agents can discover all pages through /llms.txt. Normal browser requests to URLs without .md keep the documentation layout.
For installation requirements, see versions and compatibility. If a workflow fails, start with troubleshooting.