diff --git a/.github/skills/code-review/SKILL.md b/.github/skills/code-review/SKILL.md
index 2fd41e4b3f6413..be0af82386d12b 100644
--- a/.github/skills/code-review/SKILL.md
+++ b/.github/skills/code-review/SKILL.md
@@ -105,7 +105,7 @@ When the environment supports launching sub-agents with different models (e.g.,
    - From each selected family, pick the model with the highest capability tier (prefer "premium" or "standard" over "fast/cheap").
    - Never pick models labeled "mini", "fast", or "cheap" for code review.
    - Do not select the same model that is already running the primary review (i.e., your own model). The goal is diverse perspectives from different model families.
-   - **Do not use `gpt-5.4`** — it has known reliability issues causing sub-agent timeouts in >90% of affected runs. For the OpenAI/GPT family, prefer `gpt-5.3-codex` if it is explicitly listed as available; otherwise, fall back to the highest-version non-blocked GPT model that satisfies the other rules here.
+   - **Do not use `gpt-5.4`** — it has known reliability issues causing sub-agent timeouts in >90% of affected runs.
    - If multiple standard-tier models exist in the same family (excluding blocked models above), pick the one with the highest version number. Prefer "-codex" variants over general-purpose for code review tasks.
 2. Launch a sub-agent for each selected model in parallel, giving each the same review prompt: the PR diff, the review rules from this skill, and instructions to produce findings in the severity format defined above.
 3. Wait for all agents to complete, then synthesize: deduplicate findings that appear across models, elevate issues flagged by multiple models (higher confidence), and include unique findings from individual models that meet the confidence bar. **Timeout handling:** If a sub-agent has not completed after 10 minutes and you have results from other agents, proceed with the results you have. Do not block the review indefinitely waiting for a single slow model. Note in the output which models contributed.