协作头脑风暴
brainstorming
在实现前澄清需求、探索设计选择,并形成清晰的开发方向。
server-and-conversion【开发与工程】Use MLX Audio for the API server, realtime WebSockets, Studio UI launch, and conversion or quantization workflows.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when the user needs the FastAPI/OpenAI-compatible server, realtime speech endpoints, Studio UI launch, or model conversion and quantization.
mlx_audio.server startup, API routes, and realtime WebSocket behavior.mlx_audio.convert conversion, quantization, dequantization, and upload planning.../tts-generation/.../stt-transcription/.../speech-transforms-vad/.references/server-api.md for the endpoint map and realtime model-selection rules.references/conversion.md for conversion and quantization flags.references/troubleshooting.md for dependency, protocol, and flag-mix failures.scripts/server_smoke_client.py to ping a running server.scripts/convert_command_builder.py to shape a safe conversion command.Treat the server and conversion paths as command-planning workflows first. Confirm the API surface, model id, response format, and quantization intent before starting a long-running server or conversion job.