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Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
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npx skills add https://github.com/trpc-group/trpc-agent-go --skill whisperEl comando permanece en una sola línea. Desplázate horizontalmente para revisarlo antes de copiarlo.
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Use this skill when the user asks about release dates, release owners, rollout status, or launch checklist details.
Delegate coding tasks to Codex, Claude Code, or Pi agents via background host sessions. Use when: (1) building or creating new features or apps, (2) reviewing PRs or parallel coding with managed worktree isolation when subagents are available, (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat, or any work in ~/clawd workspace (never spawn agents here). Requires OpenClaw host tools with exec_command plus write_stdin.
Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5] [--notify-channel -1002381931352]
Basado en la clasificación ocupacional SOC
Mostrando SKILL.md
| name | whisper |
| description | Transcribe audio files to text using OpenAI Whisper |
Transcribe audio files to text using OpenAI Whisper.
python3 scripts/transcribe.py <audio_file> <output_file>
# Specify model size (default: base)
python3 scripts/transcribe.py audio.mp3 transcript.txt --model medium
# Specify language (improves accuracy)
python3 scripts/transcribe.py audio.mp3 transcript.txt --language zh
# Include timestamps
python3 scripts/transcribe.py audio.mp3 transcript.txt --timestamps
# JSON output with metadata
python3 scripts/transcribe.py audio.mp3 output.json --format json
audio_file (required): Path to input audio fileoutput_file (required): Path to output text/JSON file--model: Whisper model size (tiny/base/small/medium/large, default: base)--language: Language code (e.g., en, zh, es, fr, auto for detection)--timestamps: Include word-level timestamps in output--format: Output format (text/json, default: text)| Model | Parameters | Speed | Accuracy | Memory |
|---|---|---|---|---|
| tiny | 39M | ~32x | Good | ~1GB |
| base | 74M | ~16x | Better | ~1GB |
| small | 244M | ~6x | Great | ~2GB |
| medium | 769M | ~2x | Excellent | ~5GB |
| large | 1.5B | 1x | Best | ~10GB |
MP3, WAV, M4A, FLAC, OGG, AAC, WMA, and more (via FFmpeg)
pip install openai-whisper
sudo apt-get install ffmpeg # Ubuntu/Debian