> ## Documentation Index > Fetch the complete documentation index at: https://docs.decimal.ai/llms.txt > Use this file to discover all available pages before exploring further. # Get a trace > Get a single trace with its full span tree and LLM calls. Pass `?include=eval_scores` to embed the trace's eval scores inline. Without that param, the scores live at GET /traces/{id}/eval-scores (API-001 fix — they were previously only at the sub-endpoint). ## OpenAPI ````yaml /openapi.json get /api/v1/traces/{trace_id} openapi: 3.1.0 info: title: DecimalAI Platform description: Agent Dataset Lifecycle Platform — Backend API version: 0.1.0 servers: [] security: - BearerAuth: [] tags: - name: traces description: >- Ingest, search, and inspect agent execution traces. A trace is the atomic unit of the platform — every other feature (evaluation, compatibility scoring, dataset building) operates on traces. Each trace is auto-tagged with the manifest hash of the agent that produced it. - name: eval-scores description: >- Push, fetch, and aggregate per-trace evaluation scores. Scores carry source provenance (built-in, DeepEval, LangSmith, custom) and feed the unified decision engine, which produces a keep / repair / replay / drop verdict per trace. - name: skills description: >- Manage reusable instruction blocks (SKILL.md files) that modify agent behavior. Skills are first-class manifest components — changes to a skill appear in your regression-check impact reports. Use these endpoints to create, version, fork, and sync skills with your local SKILL.md files. - name: manifests description: >- Register and inspect manifest versions. A manifest is a snapshot of your agent's structural identity (tools, prompts, models, skills) at a point in time. The SDK registers manifests automatically; these endpoints expose the underlying records. - name: datasets description: >- Build versioned SFT/DPO training datasets from manifest-classified, eval-scored traces. Datasets are reproducible — each version locks the manifest and filter set used to build it. Export as JSONL, Parquet, or push to HuggingFace Hub. - name: replay description: >- Re-execute historical traces against a new manifest version. Replay is the deferred-future capability for behavioral verification of agent changes. The SDK creates a replay batch, your worker executes each task, then submits results back here for eval scoring. - name: registry description: >- Browse and install community skills from the public skills registry. Each registry skill carries a SkillScore — an evidence-tiered quality composite computed from real-world evals, benchmarks, and ratings across organizations. Installing creates a fork in your org — edits don't affect the public version. - name: agents description: >- List and inspect agents, plus their multi-agent topology (orchestrator → sub-agent edges discovered from traces). Agents are identified by a stable agent_name string set in your SDK init() call. - name: import description: >- Bulk-import historical traces from another observability platform or a JSONL backup. Useful for migrating from LangSmith / Braintrust / Langfuse. Duplicate trace IDs are silently skipped — re-running an import is safe. paths: /api/v1/traces/{trace_id}: get: tags: - traces summary: Get a trace description: |- Get a single trace with its full span tree and LLM calls. Pass `?include=eval_scores` to embed the trace's eval scores inline. Without that param, the scores live at GET /traces/{id}/eval-scores (API-001 fix — they were previously only at the sub-endpoint). operationId: get_trace_api_v1_traces__trace_id__get parameters: - name: trace_id in: path required: true schema: type: string title: Trace Id - name: include in: query required: false schema: anyOf: - type: string - type: 'null' description: 'Comma-separated extras: eval_scores' title: Include description: 'Comma-separated extras: eval_scores' - name: Authorization in: header required: false schema: type: string title: Authorization - name: decimal_session in: cookie required: false schema: anyOf: - type: string - type: 'null' title: Decimal Session responses: '200': description: Successful Response content: application/json: schema: type: object additionalProperties: true title: Response Get Trace Api V1 Traces Trace Id Get example: id: trc_abc123 agent_name: travel-planner status: success user_input: Find flights to Tokyo final_output: I found 3 flights to Tokyo. manifest_id: mfst_001 eval_verdict: keep eval_score: 0.92 started_at: '2026-05-10T14:22:00Z' ended_at: '2026-05-10T14:22:01Z' duration_ms: 1240 total_tokens: 850 spans: - id: s1 name: agent-step span_type: agent status: success started_at: '2026-05-10T14:22:00Z' llm_calls: - id: l1 span_id: s1 model_name: gpt-4o input_tokens: 500 output_tokens: 350 '400': description: Malformed trace_id (not a UUID). '404': description: Trace not found. '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' x-codeSamples: - lang: Python label: Python SDK source: |- import httpx resp = httpx.get( "https://api.decimal.ai/api/v1/traces/trc_abc123", headers={"Authorization": "Bearer dai_sk_..."}, params={"include": "eval_scores"}, # optional ) resp.raise_for_status() trace = resp.json() - lang: Bash label: CLI source: decimalai traces show trc_abc123 components: schemas: HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type input: title: Input ctx: type: object title: Context type: object required: - loc - msg - type title: ValidationError securitySchemes: BearerAuth: type: http scheme: bearer description: Enter your API key (e.g. dai_sk_test_key_001) ````