chore: drop added comments and docstrings

strix/core/execution.py

@@ -84,9 +84,6 @@ async def _compact_session(
     )
 
 
-# Retryable HTTP statuses for a model/provider call: request timeout + 5xx server errors.
-# 429 is intentionally excluded here; a persistent rate limit is handled as a graceful,
-# resumable scan stop in ``runner.run_strix_scan``.
 _TRANSIENT_MODEL_STATUS_CODES = frozenset({408, 500, 502, 503, 504})
 _MAX_TRANSIENT_MODEL_RETRIES = 4
 _TRANSIENT_MODEL_RETRY_BASE_DELAY_S = 2.0
@@ -99,21 +96,6 @@ def _model_error_status_code(exc: BaseException) -> int | None:
 
 
 def _is_transient_model_error(exc: BaseException) -> bool:
-    """Return whether a model/provider error is a transient upstream failure worth replaying.
-
-    Three families are treated as transient:
-
-    * network-level faults reaching the provider (connection reset, read timeout);
-    * retryable HTTP statuses (request timeout + 5xx) surfaced as ``APIStatusError``;
-    * mid-stream provider errors, where the server injects an ``{"error": ...}`` frame into
-      an already-200 SSE stream and the OpenAI SDK raises a bare ``APIError`` with no status
-      code. The agents SDK cannot replay these once tokens have streamed, so an untreated
-      one propagates and crashes the whole scan.
-
-    A persistent rate limit is deliberately excluded (handled as a graceful scan stop at the
-    runner level), as are permanent 4xx client errors (they carry a status code and are
-    surfaced as ``APIStatusError``).
-    """
     if isinstance(exc, RateLimitError):
         return False
     if isinstance(exc, APITimeoutError | APIConnectionError):
@@ -554,8 +536,6 @@ async def _run_cycle(  # noqa: PLR0912, PLR0915
                     exc,
                 )
                 await asyncio.sleep(delay)
-                # The turn's input was already persisted to the session before the model
-                # call, so replay from session state to avoid duplicating it.
                 if session is not None:
                     input_data = []
                 continue

tests/test_execution_transient_retry.py

@@ -1,10 +1,3 @@
-"""Tests for transient model/provider error replay in the agent run cycle.
-
-A transient upstream error (e.g. a mid-stream ``openai.APIError`` injected into an
-already-200 SSE stream) must be retried at the turn level instead of crashing the
-whole scan, while permanent errors and rate limits keep their existing behavior.
-"""
-
 from __future__ import annotations
 
 from typing import Any, cast
@@ -31,7 +24,6 @@ def _request() -> httpx.Request:
 
 
 def _midstream_api_error() -> APIError:
-    """A bare APIError with no status code — the mid-stream generic provider error."""
     return APIError("An error occurred while processing the request.", _request(), body=None)
 
 
@@ -64,7 +56,6 @@ def test_server_errors_are_transient() -> None:
 
 
 def test_rate_limit_is_not_retried_here() -> None:
-    # A persistent rate limit is handled as a graceful scan stop at the runner level.
     rate_limited = RateLimitError(
         "slow down", response=httpx.Response(429, request=_request()), body=None
     )
@@ -81,8 +72,6 @@ def test_client_errors_are_not_transient() -> None:
 
 
 class _FakeStream:
-    """Minimal stand-in for a streamed run result."""
-
     def __init__(self, exc: BaseException | None = None) -> None:
         self._exc = exc
         self._events: list[Any] = []
@@ -137,7 +126,6 @@ async def _run_once(
 async def test_run_cycle_retries_transient_midstream_error(
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
-    """A transient mid-stream error is replayed and the turn then succeeds."""
     streams = [_FakeStream(exc=_midstream_api_error()), _FakeStream()]
     result, attempts, _coordinator = await _run_once(monkeypatch, streams)
 
@@ -149,7 +137,6 @@ async def test_run_cycle_retries_transient_midstream_error(
 async def test_run_cycle_gives_up_after_max_retries(
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
-    """Persistent transient errors exhaust the bound, then propagate (non-interactive)."""
     streams = [
         _FakeStream(exc=_midstream_api_error())
         for _ in range(execution._MAX_TRANSIENT_MODEL_RETRIES + 1)
@@ -162,7 +149,6 @@ async def test_run_cycle_gives_up_after_max_retries(
 async def test_run_cycle_does_not_retry_permanent_error(
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
-    """A permanent client error is not replayed; it propagates on the first attempt."""
     bad_request = BadRequestError(
         "bad", response=httpx.Response(400, request=_request()), body=None
     )