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Welcome to Tuor

Welcome to the developer documentation for Tuor — a full-stack platform for storing model traces and managing human review.

Tuor sits between your model and your reviewers. You log every model call as a trace; reviewers approve, reject, or correct the output in a purpose-built review workspace; and reviewed data flows back to you as webhook events or a streaming JSONL export — ready to feed dashboards, evals, or training pipelines.

Documentation map

Docs — start here

  • Getting Started — Create a project, get an API key, send your first trace.
  • Core Concepts — Traces, outcomes, payload shapes, and result delivery.

Reference — integration details

  • Integration API — Send traces, fetch review results, tag cohorts, and export reviewed data.
  • Webhooks — Receive real-time review verdicts with signature verification.

Guides — integration patterns

  • Reviewer Blueprints — Structure payloads so reviewers can work fast and accurately.
  • Dynamic Prompts — Advanced: fetch the active prompt at runtime and link traces to the prompt version that produced them.

What does Tuor do, at a glance?

flowchart LR
    A[Your App] -->|POST /v1/traces| B[Tuor]
    B --> C[Review Workspace]
    C -->|approve / reject / correct| B
    B -->|Outbound Webhook| A
    B -->|GET /v1/traces/export| D[Fine-Tuning / Eval Pipeline]
  • Ingest every model call (input + output + config) with one HTTP request.
  • Review in a workspace designed for non-technical experts: project-scoped trace lists, correction editors, saved diffs, PDF viewers, and image viewers.
  • Receive signed webhooks the moment a verdict lands, or stream the entire reviewed corpus as JSONL.

Conventions used in this documentation

  • All API examples use https://api.tuor.dev as the base URL.
  • All programmatic endpoints are versioned under /v1/.
  • The full documentation corpus is available as llms-full.txt.

If you spot a gap or inaccuracy in these docs, contact Tuor support.