How do I evaluate a subagent separately from the main loop?

Grade the subagent’s own final message, carried back to the parent as the Agent tool’s result, rather than whatever the parent agent says afterward. A subagent’s intermediate tool calls and reasoning stay inside its own isolated context and never reach the parent; only that one final message crosses the boundary, and the parent is free to summarize or rephrase it before it reaches the user, so a check run on the parent’s reply is really grading the parent’s paraphrase, not the subagent’s actual work.

Messages carry a parent_tool_use_id field that ties them back to the subagent that produced them, which is what lets a grader pull just that subagent’s output out of the stream instead of the whole session. A subagent’s transcript is also stored separately from the parent’s and can be resumed on its own, so a failing case can be replayed at the point the subagent actually went wrong. Grading one node of a LangGraph graph is the same idea applied to a different framework’s unit of delegation.

sources

keep reading

More on this.

Two ways to run Tessary.

Tessary is an open-source agent reliability platform. Cloud and self-hosted run the same workflow on the OpenTelemetry traces your agent already emits.

Tessary Cloud

We host it for you. Send your first trace with nothing to deploy and no model key.

what's includedper organization
traces
10,000 per calendar month
stored trace data
1 GB
retention
30 days
model credit
$10, one-time, for triage and root-cause analysis
credit card
not required

Self-hosted Tessary

Run the open-source code on your own infrastructure with one command. Add your own model key for triage and root-cause analysis.

Self-host Tessary for me by following https://github.com/tessaryai/tessary/blob/main/setup.md

docker compose -f oci://docker.io/tessaryai/tessary:compose up -d -y