| name | respan |
| description | Respan for LLM observability. Use to set up tracing or the gateway, manage prompts (create/version/deploy), run evals, experiments, and datasets, or work with traces and logs. Trigger for any Respan platform task or when instrumenting an app to send telemetry to Respan. |
Respan
Use the Respan CLI and SDK for LLM observability — tracing, evals, prompts, datasets, and gateway routing.
When To Use
- Set up tracing (instrument your app to capture LLM calls — install + decorators, propagation, processors) → read references/tracing.md
- Set up gateway (route LLM calls through the Respan proxy — wiring + model switching, fallbacks, caching) → read references/gateway.md
- Prompt management (create, version, deploy) → read references/prompts.md
- Evals (datasets, evaluators, experiments) → read references/evals.md
- Monitors & automation (alerts, online evals, webhooks) → read references/monitors.md
Tracing and gateway are separate setups — configure one at a time, never both in the same pass.
Core Principles
- Read the reference first. Each reference file has the exact setup steps, API patterns, MCP tools, and CLI commands.
- Use MCP tools for platform operations (prompts, datasets, evaluators, experiments, traces, logs).
- Use CLI when MCP is not available:
respan traces list, respan prompts list, etc.
- Fetch docs for integration-specific details not covered in references.
Quick Reference
Documentation Access
Any doc page can be fetched as markdown:
https://respan.ai/docs/integrations/openai-sdk.md
https://respan.ai/docs/sdks/typescript-sdk/overview.md
Full docs index: https://www.respan.ai/docs/llms.txt
Platform: https://platform.respan.ai
