Observability

DSAgt logs traces to a MLflow via an SQLite file at ~/dsagt-projects/<project>/mlflow.db. To view in the MLflow UI:

dsagt traces <project> # rund dsagt mlflow ui --backend-store-uri sqlite:///<project>/mlflow.db

dsagt info <name> prints the resolved tracking URI and a session/trace summary. The tracking URI resolves as MLFLOW_TRACKING_URI env → project config → the sqlite:///<project>/mlflow.db default.

Two feeds

DSAgt reconstructs traces from what the agent writes to disk. Traces come from two places:

1. DSAgt spans (live). DSAgt instruments its own code and emits spans directly to the store as it runs.
2. Agent traces (post-hoc). The MCP server's in-session heartbeat reads the agent's own on-disk session transcript, translates it to a canonical trace shape, and writes it to the same store via the MLflow sink — recovering prompts, responses, and tool calls.

Trace Coverage

Source	Span type	Contents
Knowledge base	kb.search, kb.embed, kb.index_search, kb.rerank	Per-phase timing trees
Code executions	code.execute	Exit code, duration, file counts, truncated stderr. Full payload in trace_archive/<record_id>.json
Registry events	save_code_spec, install_dependencies, reconstruct_pipeline	Span metadata
Agent traces	one AGENT subtree per turn (llm / tool_<name> children)	Prompts, responses, tool calls, and token usage where the transcript carries them

Agent trace coverage

Agent traces are reconstructed from each agent's on-disk session record. A per-agent reader + translator runs for every supported agent (claude, codex, goose, opencode, cline), uniformly. Fidelity is capped by what the transcript persisted (e.g. token counts and timing appear where the agent recorded them).

Every span carries the project's session id (minted per launch into <project>/.dsagt/state.yaml) for filtering in the MLflow trace view.

The trace scan runs at periodic intervals (2m) inside the MCP server — At each interval DSAgt reads new transcript records, translates completed turns, and translates the canonical trace format to episodic memory in the knowledge base, and MLflow records in the MLFlow store.

Try it

dsagt init            # follow the prompts: name it `demo`, then pick your agent
dsagt start demo      # …run a prompt or two, then exit the agent
dsagt traces <project>

Open MLflow UI to see both feeds in one store: DSAgt's own kb.* / code.execute spans and the per-turn agent traces recovered from the transcript. dsagt info demo prints the same session/trace summary from the command line.