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/javimosch/open-claw-skills --skill audio-processing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。
Connect your AI assistant to GoHighLevel CRM via the official API v2. Manage contacts, conversations, calendars, pipelines, invoices, payments, workflows, and 30+ endpoint groups through natural language. Includes interactive setup wizard and 100+ pre-built, safe API commands. Python 3.6+ stdlib only — zero external dependencies.
Manage Cloudflare DNS records, Tunnels (cloudflared), and Zero Trust policies. Use for pointing domains, exposing local services via tunnels, and updating ingress rules.
Mema's personal brain - SQLite metadata index for documents and Redis short-term context buffer. Use for organizing workspace knowledge paths and managing ephemeral session state.
基于 SOC 职业分类
正在显示 SKILL.md
| name | audio-processing |
| description | Audio ingestion, analysis, transformation, and generation (Transcribe, TTS, VAD, Features). |
| metadata | {"openclaw":{"emoji":"🎙️","requires":{"bins":"[Truncated]","pip":"[Truncated]"},"install":["[Truncated]","[Truncated]"],"version":"1.1.0"}} |
A comprehensive toolset for audio manipulation and analysis with security validations.
Perform audio operations like transcription, text-to-speech, and feature extraction.
action (string, required): One of transcribe, tts, extract_features, vad_segments, transform.file_path (string, optional): Path to input audio file.text (string, optional): Text for TTS (max 10,000 chars).output_path (string, optional): Path for output file (default: auto-generated).model (string, optional): Whisper model size (tiny, base, small, medium, large). Default: base.ops (string, optional): JSON string of operations for transform action.Usage:
# Transcribe audio file
uv run --with "openai-whisper" --with "pydub" --with "numpy" skills/audio-processing/tool.py transcribe --file_path input.wav
# Transcribe with specific model
uv run --with "openai-whisper" skills/audio-processing/tool.py transcribe --file_path input.wav --model small
# Text-to-speech
uv run --with "gTTS" skills/audio-processing/tool.py tts --text "Hello world" --output_path hello.mp3
# Extract audio features
uv run --with "librosa" --with "numpy" --with "soundfile" skills/audio-processing/tool.py extract_features --file_path input.wav
# Voice activity detection (find speech segments)
uv run --with "pydub" skills/audio-processing/tool.py vad_segments --file_path input.wav
# Transform audio (trim, resample, normalize)
uv run --with "pydub" skills/audio-processing/tool.py transform --file_path input.wav --ops '[{"op": "trim", "start": 10, "end": 30}, {"op": "normalize"}]'
Convert speech to text using OpenAI Whisper.
{ "text": "...", "segments": [...] }Generate speech from text using Google TTS.
{ "file_path": "output.mp3", "status": "created" }Extract audio features for analysis.
Detect speech segments using silence detection.
{ "segments": [{ "start": 0.5, "end": 3.2 }, ...] }Apply transformations to audio files.
{ "file_path": "output.wav" }