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在 OpenClaw 中安装
/install local-llama-tts
功能描述
Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model.
使用说明 (SKILL.md)
Local Llama TTS
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] "\x3Ctext>"
Options
-o, --output \x3Cfile>: Output WAV file (default:output.wav)-s, --speaker \x3Cfile>: Speaker reference file (optional)-t, --temp \x3Cvalue>: 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
- Model: Download from OuteAI/OuteTTS-1.0-0.6B-GGUF
- Vocoder: Download from ggml-org/WavTokenizer (Note: Felix uses a Q4_0 version, Q5_1 is linked here as a high-quality alternative).
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
安全使用建议
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 any downloaded binary as root and review the binary's behavior if you plan to allow autonomous agent invocation. The script itself contains no network exfiltration or unrelated credential access.
功能分析
Type: OpenClaw Skill
Name: local-llama-tts
Version: 1.0.0
The `scripts/tts-local.sh` script is vulnerable to shell injection. The `$SPEAKER_PARAM` variable is constructed using user-supplied input (the speaker file path) and then expanded unquoted in the final `llama-tts` command. This allows an attacker to inject arbitrary shell commands by providing specially crafted input to the `-s` or `--speaker` option, leading to potential remote code execution if the agent executes this skill with untrusted input.
能力评估
Purpose & Capability
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.
Instruction Scope
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.
Install Mechanism
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).
Credentials
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.
Persistence & Privilege
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.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install local-llama-tts - 安装完成后，直接呼叫该 Skill 的名称或使用
/local-llama-tts触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
常见问题
Local Llama TTS 是什么？
Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 832 次。
如何安装 Local Llama TTS？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install local-llama-tts」即可一键安装，无需额外配置。
Local Llama TTS 是免费的吗？
是的，Local Llama TTS 完全免费（开源免费），可自由下载、安装和使用。
Local Llama TTS 支持哪些平台？
Local Llama TTS 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Local Llama TTS？
由 wuxxin（@wuxxin）开发并维护，当前版本 v1.0.0。
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