Port Google Research's Harness^2 method layer (model weights frozen,
only the surrounding harness is optimized): Propose-Probe-Compose with
INV/DOM/AGG editors, parallel/sequential modes, per-domain experience
library, anonymous-product selection, k<=3 hard cap and budget gate.
Execution goes only through the existing control-plane API (upload ->
task with idempotency key -> poll -> trace/cost -> cancel on timeout);
no new server endpoints, no codex flags composed, tasks inherit the
normal executor/sandbox/quota/audit path.
Wiring lessons from four real rounds against production (project
wwww, ledger task): HttpTaskClient retries transient disconnects and
502/503/429 (3 attempts); editors get a worked file-block example, an
explicit <no-change> marker and one feedback retry (.fmt2) instead of
silently accepting notes-only replies; run_task unwraps the server's
result_text JSON envelope (text field holds the real reply) — without
this, line-anchored file-block parsing could never see blocks the
agents were actually emitting. Final round (real4) fully green:
all stages landed, selection non-fallback, experience入库, probe
delivers the correct signed total 85.15.
Tests: 35 harness tests (17 method + 18 wiring incl. fake-control-plane
full round, idempotent replay, retry, format retry, envelope round).
Deliberate deviations from upstream are documented in docs/harness2.md
(no network-unrestricted/sandbox-disabled defaults, auto_apply off,
no benchmark/scorer, probe deliverable = final reply text).
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