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Closes #6. Same model-agnostic seam as #8 but for tool-call markers (`<tool_call>` / `</tool_call>` on Qwen3-Coder, Hermes-format, DeepSeek-Coder, gpt-oss, …). Lets Zed's tool-use feature and any other vanilla OpenAI chat client get structured `tool_calls` deltas out of cortex without having to parse markers themselves. ## Implementation 1. **Tokenizer probe at load time** (`detect_tool_call_token_pair` in `wire::event`) — same shape as the reasoning-marker probe from #8. Both open AND close must resolve to single token ids; non-tool-use models get `None` and pass through unchanged. Stored on `LoadedModel.tool_call_tokens` and the TP analogue. 2. **New `InferenceEvent::ToolCall` variant** — carries `index` (call slot, per-turn counter), generated `id` (`call_<hex>_<idx>`), `name`, and the complete `arguments` JSON string. One event per parsed call. 3. **Token-level state machine** in all three streaming paths (CPU `run_inference_streaming`, CUDA single-GPU `stream_inference_via_worker`, CUDA TP `chat_completion_tp_stream`) layered on top of #8's reasoning routing: - `<tool_call>` token → enter buffering state, clear buffer. - Tokens while buffering → accumulate into `tool_call_buf` via the decoder (so multi-byte UTF-8 still buffers correctly) without emitting anything visible. - `</tool_call>` token → take the buffer, parse with `parse_tool_call_body` (extract `name` + `arguments`), emit a structured `ToolCall` event with a fresh `call_<hex>` id and the parsed fields. - On parse failure → fall back to re-emitting the original `<tool_call>{buf}</tool_call>` block as plain text content so helexa-acp's existing `ToolCallParser` repair passes still have a chance to recover the call. 4. **OpenAI chat projector** emits the OpenAI streaming `tool_calls` delta shape on `InferenceEvent::ToolCall` — `{tool_calls: [{index, id, type:"function", function:{name, arguments}}]}`. One chunk per call slot. 5. **OpenAI Responses projector** drops `ToolCall` events for now (Responses-side function_call event family routing tracked under #7); the chat path is what unblocks Zed's tool use today. ## Acceptance - Vanilla OpenAI chat clients (Zed's tool-use feature, any other OpenAI-compatible tool-call consumer) get structured tool_calls deltas against cortex+neuron without having to parse `<tool_call>` markers in content. - helexa-acp continues to work — when neuron parses cleanly, it consumes the structured deltas through its existing decoder. When the model emits malformed JSON, neuron falls back to text pass-through and helexa-acp's `ToolCallParser` recovers via the same path it always did. - Models without tool-call markers in their tokenizer pass through unchanged. - No hardcoded model knowledge — entirely driven by tokenizer metadata. ## Tests 2 new detection tests in `wire::event` (Qwen3-style marker detection, no-marker case). The streaming paths themselves stay covered by the existing chat-completions integration tests; full end-to-end exercise of the new path requires GPU-loaded models and lives outside the CI test surface. 215 workspace tests pass; clippy + fmt clean across the workspace. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>