gpt-5.5 via codex runtime silently drops tool calls on conversational turns — anyone else seeing this?

Running OpenClaw with gpt-5.5 as the main agent model (via the codex agentRuntime). Started seeing the bot go silent — typing indicator flashes briefly, no reply. Dug into the trajectory JSONL and found the pattern: **Working run:** ``` session.started → context.compiled → prompt.submitted → tool.call (message, action=send) → tool.result → model.completed → session.ended ``` **Silent run:** ``` session.started → context.compiled → prompt.submitted → model.completed → session.ended ``` The model IS responding — there's coherent `assistant/text` content in the session file. It just never calls the `message` tool to deliver it. Status is `success`, no errors anywhere in the log. Observed on short conversational turns ("summarize X", "hello?", "u back?" — 6–16 chars). A longer, more substantive message in the same session got a proper tool call right before the drops started. Session was at ~138k tokens when it began. Switching primary to `deepseek/deepseek-v4-pro` fixed it immediately. A few questions: - Anyone else seen gpt-5.5 drop `message` tool calls specifically on short turns? - Is this a known regression or context-load behavior? - Is there something in the codex agentRuntime prompt/tool definition that reinforces tool-call adherence that might have drifted? Worth noting: a `/model` switch from Telegram doesn't recover it because the `codex-app-server.json` thread binding keeps the session pinned to gpt-5.5. Requires SSH to sever the thread and restart. I know 5.5 has regressed recently for even non-openclaw applications but this is my first observation of regression with this frontier model. EDIT1: i’m on v2026.5.20. wonder if OAuth vs API path matters here.