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/install local-llama-tts
Description
Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model.
README (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
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install local-llama-tts - After installation, invoke the skill by name or use
/local-llama-tts - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is Local Llama TTS?
Local text-to-speech using llama-tts (llama.cpp) and OuteTTS-1.0-0.6B model. It is an AI Agent Skill for Claude Code / OpenClaw, with 832 downloads so far.
How do I install Local Llama TTS?
Run "/install local-llama-tts" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Local Llama TTS free?
Yes, Local Llama TTS is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Local Llama TTS support?
Local Llama TTS is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Local Llama TTS?
It is built and maintained by wuxxin (@wuxxin); the current version is v1.0.0.
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