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🔊 Local Llama TTS — 技能工具

v1.0.0

Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model.

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by @wuxxin·MIT-0
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License
MIT-0
最后更新
2026/4/11
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OpenClaw
安全
high confidence
The skill is internally coherent: it wraps a local llama-tts binary to synthesize speech from a local model file and its scripts/instructions match that purpose.
评估建议
This skill appears to do what it says: run your local 'llama-tts' binary against local model files. Before installing or running it: 1) Verify the 'llama-tts' binary you use is from a trusted source and inspect its permissions; 2) Download model/vocoder files from the official Hugging Face pages and verify checksums/licensing; 3) Prefer placing models in a user-controlled directory rather than a global /data/public/... path to avoid accidental exposure or overwrites; 4) Be cautious about running...
详细分析 ▾
✓ 用途与能力
Name and description describe local TTS. The only required binary is 'llama-tts' and the included script invokes that binary with model and vocoder files — this is proportionate to the claimed purpose.
ℹ 指令范围
SKILL.md and the script only run the local 'llama-tts' binary and ask you to download models from Hugging Face. Minor notes: the recommended model/vocoder paths are hardcoded to /data/public/machine-learning/models/text-to-speach/, which may be a shared/global path; instructions include a different vocoder release (Q5_1) than the vocoder filename used in the script (Q4_0) but the SKILL.md comments this as an alternative. No instructions request unrelated files, credentials, or external endpoints beyond model download links.
✓ 安装机制
No install spec — instruction-only plus a wrapper script. This is low-risk; nothing in the skill tries to fetch or execute code during install. Model downloads are documented but performed by the user (via Hugging Face links).
✓ 凭证需求
The skill requests no environment variables or credentials. The resources referenced (local model and vocoder files, llama-tts binary) are relevant and necessary for local TTS.
✓ 持久化与权限
The skill does not request always:true, does not modify other skills, and does not try to persist credentials. It is user-invocable and can be invoked autonomously by the agent (platform default) — nothing here elevates privilege beyond expected behavior.
安全有层次，运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发，无需署名。

运行时依赖

无特殊依赖

版本

latestv1.0.02026/2/17

Initial release

● 可疑

安装命令 点击复制

官方npx clawhub@latest install local-llama-tts
镜像加速npx clawhub@latest install local-llama-tts --registry https://cn.clawhub-mirror.com

技能文档

Synthesize speech locally using llama-tts and the OuteTTS-1.0-0.6B model.

Usage

You can use the wrapper script:

  • scripts/tts-local.sh [options] ""

Options

  • -o, --output : Output WAV file (default: output.wav)
  • -s, --speaker : Speaker reference file (optional)
  • -t, --temp : Temperature (default: 0.4)

Scripts

  • Location: scripts/tts-local.sh (inside skill folder)
  • Model: /data/public/machine-learning/models/text-to-speach/OuteTTS-1.0-0.6B-Q4_K_M.gguf
  • Vocoder: /data/public/machine-learning/models/text-to-speach/WavTokenizer-Large-75-Q4_0.gguf
  • GPU: Enabled via llama-tts.

Setup

Place files in /data/public/machine-learning/models/text-to-speach/ or update scripts/tts-local.sh.

Sampling Configuration

The model card recommends the following settings (hardcoded in the script):
  • Temperature: 0.4
  • Repetition Penalty: 1.1
  • Repetition Range: 64
  • Top-k: 40
  • Top-p: 0.9
  • Min-p: 0.05
数据来源：ClawHub ↗ · 中文优化：龙虾技能库
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