fix(yolo-skill): don't require ultralytics on mps when framework_ok is False

[solderzzc]

Summary

• load_optimized()'s final fallback branch (taken when the optimized runtime check fails, framework_ok=False) unconditionally imported ultralytics — but mps installs deliberately never ship torch/ultralytics (requirements_mps.txt only lists onnxruntime).
• Any mps machine where _check_mps_runtime() fails (CoreML execution provider not found) crashed with No module named 'ultralytics' when loading a YOLO skill, instead of falling back to the pre-built .onnx model via plain CPUExecutionProvider.
• This is one of the bugs reported in SharpAI/DeepCamera#207 — the reporter's exact traceback (Failed to load model: No module named 'ultralytics', backend=mps, framework_ok=False) reproduces this path exactly.

Fix

On the mps backend, that fallback branch now calls _load_onnx_coreml() (already used elsewhere in the same function for the mps happy path) against the pre-built .onnx, instead of assuming ultralytics is importable. If no pre-built .onnx exists either, it raises a clear RuntimeError instead of a confusing ModuleNotFoundError.

Applied identically to both copies of env_config.py (skills/detection/yolo-detection-2026/scripts/ and skills/lib/), matching how #194 touched both.

Test plan

• New regression test skills/lib/test_env_config_mps_fallback.py (3 tests) — reproduces the exact reported log conditions (backend=mps, framework_ok=False), asserts the ONNX CoreML path is used instead of importing ultralytics, and asserts a clear error when no pre-built model exists.
• Ran full skills/lib/test_env_config_*.py suite — 4 pre-existing failures in test_env_config_ane.py reproduce identically on develop without this change (unrelated to this fix, not introduced by it).
• Not yet verified against Brian's actual machine/log — worth confirming with a targeted build the way Says SwiftLM Not Installed #207's other fixes were (0.2.10–0.2.14).

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