AgentClash

Trace to dataset

Turn production agent traces into datasets

The best seed material often comes from real agent runs. DataSmith ingests OTLP JSON and span JSONL locally for training export. AgentClash imports traces into workspace datasets for eval baselines and CI gates.

live eval
gate: pass

Candidate

92correct patch, low cost

Baseline

88stable reference run

Control

73missed edge case

replay timeline

1loaded task inputs and tool policy
2ran sandbox actions and captured artifacts
3scored trajectory and validator evidence
4attached scorecard and release verdict

ci verdict

Candidate clears release gate

Correctness improved, latency within budget, and required artifacts were preserved for review.

agentclash run create --follow

Two paths from traces

Built for reviewable agent decisions

Training teams use DataSmith ingest-otel for SFT and DPO pipelines. Platform teams use AgentClash trace import to promote production failures into regression coverage.

OpenTelemetry-compatible trace import

Pinned datasets and golden test cases

Baseline versus candidate regression checks

Replay trails for tool calls, outputs, and artifacts

Scorecards for correctness, cost, latency, and evidence

CI gates for prompt, model, RAG, and tool changes

Workflow

Trace ingestion workflow

Import the evidence

Start from OpenTelemetry traces, curated datasets, support transcripts, or a real failure your team already saw.

Pin the baseline

Record the current accepted behavior so every prompt, model, RAG, or tool change has a fair comparison point.

Replay the evidence

Inspect tool calls, outputs, artifacts, latency, cost, and judge evidence when a candidate gets worse.

Gate the release

Compare candidate and baseline runs, then fail CI before a regression reaches users.

FAQ

Trace to dataset FAQ

What trace formats does DataSmith support?

OTLP JSON exports and flattened span JSONL. See the DataSmith docs/otel.md guide for field expectations.

Does AgentClash import the same traces?

AgentClash supports OTel-compatible trace import into workspace datasets for eval and regression workflows, complementary to DataSmith training export.

Should traces become seeds or finished examples?

Usually seeds. Run Agentic Self-Instruct afterward to expand grounded, judge-filtered examples rather than training on raw spans alone.