Two coupled changes responding to the 2026-05-22 batch's tier-0 hit
rate of 0% on PRs the estimator judged "simple", plus three spurious
worker-internal-errors caused by the estimator's MCP-finalize wall
clock exceeding the previous 30s budget.
agent_runner.py — finalize timeout
----------------------------------
`production_agent_runner` previously hardcoded `finalize_timeout_s=30.0`.
On the 8-PR batch the worker recorded three `worker-internal-error`
attempts (PRs 47, 50, 54) all with the same message:
role='estimator' did not emit canonical output within 30.0s ...
The retries succeeded with estimator self-time of 41.5s, 25.9s, 21.5s —
all within plausible bounds for a multi-subsystem PR (PR 54 needed
41.5s of reasoning + MCP IPC + finalize write). Each spurious timeout
cost ~90s of worker wallclock + a re-dispatch.
New module-level constant `_DEFAULT_FINALIZE_TIMEOUT_S` reads
`CONTROLLER_FINALIZE_TIMEOUT_S` (default 90s), matching the
`CONTROLLER_*_TIMEOUT_S` convention used by `opencode_session.py`.
Operators can tune via `.devcontainer/.env.{fork,prod}`.
estimator-implementation.md — TIER MAP + CALIBRATION
----------------------------------------------------
The estimator was wrong on 4 of 8 PRs in the May-22 batch, all in
the same direction (recommended tier 0, escalated to tier 1).
Three of the four were high-confidence picks — including a PR
described as "4 string constant replacements, isolated scope, no
logic changes" that still got bounced at tier 0.
Three prompt changes:
- TIER MAP rewritten: tier 1 is now the default for non-trivial
work; tier 0 requires positive evidence the change is mechanical
(single file, ≤50 LOC, no new logic, no test changes).
- CONFIDENCE RULES "When uncertain, prefer" flipped tier 0 → tier 1.
- New CALIBRATION section bakes in the empirical observation (0/4
hit rate, why Haiku struggles in this codebase, cost calculus:
wrong tier-1 < wrong tier-0 by an order of magnitude when measured
per merged PR).
tiers.yaml — clarify scope
--------------------------
The previous "Used by estimator-implementation.md to make tier
choices model-agnostic" comment on the `capability` field misled
readers into thinking tiers.yaml drove classification. It doesn't —
the estimator agent reads its TIER MAP from its own prompt and
emits an integer; tiers.yaml only answers "for tier-N, which model
runs?". Updated header + field comments to flag this clearly so
future operators don't change descriptors here expecting the
estimator to honor them.
Tests
-----
+ test_default_finalize_timeout_reads_env: covers the env-var
resolution for `CONTROLLER_FINALIZE_TIMEOUT_S` (default, override,
float values). Restores the default at the end so subsequent
tests in the session see the stock constant.
Existing tier-model registry + 27 agent_runner tests pass unchanged.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
drew
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