用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/duclm1x1/Dive-Ai --skill mlx-stt命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
正在显示 SKILL.md
| name | mlx-stt |
| description | Speech-To-Text with MLX (Apple Silicon) and GLM-ASR-Nano-2512 locally. |
| metadata | {"openclaw":{"always":true,"emoji":"🦞","homepage":"https://github.com/guoqiao/skills/blob/main/mlx-stt/mlx-stt/SKILL.md","os":["darwin"],"tags":["latest","asr","stt","speech-to-text","audio","glm","glm-asr","glm-asr-nano-2512","glm-asr-nano-2512-8bit","macOS","MacBook","Mac mini","Apple Silicon","mlx","mlx-audio"],"requires":{"bins":["brew"]}}} |
Speech-To-Text/ASR/Transcribe with MLX (Apple Silicon) and GLM-ASR-Nano-2512 locally.
Free and Accurate. No api key required. No server required.
mlx: macOS with Apple Siliconbrew: used to install deps if not availablebash ${baseDir}/install.sh
This script will use brew to install these cli tools if not available:
ffmpeg: convert audio format when neededuv: install python package and run python scriptmlx_audio: do the real jobTo transcribe an audio file, run the mlx-stt.py script:
uv run ${baseDir}/mlx-stt.py <audio_file_path>
mlx-community/GLM-ASR-Nano-2512-8bit, 2.5GB ish.Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.