aed114a69 taught _is_synthetic_compression_user_turn to recognize the
max-iteration nudge as ephemeral runtime scaffolding rather than a human
turn, since its role="user" metadata flag doesn't survive SessionDB
projection and a crash/interrupt mid-turn can persist it durably — becoming
the compaction anchor / auto-focus topic in place of the real task.
conversation_loop.py's retry loop appends several more role="user" rows
with the exact same "ephemeral, metadata-tag-only" shape, none of them
recognized by the classifier:
- The three _get_continuation_prompt variants (length-continuation nudge,
tagged _length_continuation_nudge) — two fixed strings plus a third that
interpolates the dropped-tool-call list.
- _CODEX_INCOMPLETE_NUDGE (codex/responses reasoning-only retry).
- The codex ack-continuation nudge (acknowledgment-only reply re-prompt).
- The dropped-tool-call nudge (tagged _dropped_toolcall_nudge) — persisted
across up to 3 consecutive retries before the finalization pop-loop
strips it; an interrupt/crash before that pop can persist it same as the
max-iteration case.
Promote the previously-inline nudge strings to named module-level constants
in conversation_loop.py (single source of truth for both construction and
recognition), then extend the classifier to recognize all of them — exact
match for the five fixed-content nudges, a stable-prefix check for the
dropped-tool-call continuation variant (its tool list is interpolated so it
can't be exact-matched, same treatment TODO_INJECTION_HEADER already gets).
Imported lazily inside the classifier to avoid a module-load-order cycle —
conversation_loop.py already imports FROM context_compressor.py at call
time for the same reason.
pierrenode
45cd93fb5b