Mimo Tts Asr

Xiaomi MiMo V2.5 TTS + ASR 全能语音技能。支持高质量中英文语音合成（TTS）和语音识别（ASR）。 TTS: 三款模型（精品音色 / VoiceDesign 音色设计 / VoiceClone 音色克隆）、方言支持、情感控制、多格式输出。 ASR: 音频转文字、多语言识别、方言、Code...

This skill appears to implement the advertised MiMo TTS and ASR features, but there are a few things to check before installing: - Provenance: The SKILL.md links to Xiaomi/MiMo domains, but the package author/owner in metadata is not clearly an official Xiaomi account. Verify the skill's source (official repo or vendor) before trusting it. - API keys: The scripts require MIMO_API_KEY and/or MIMO_ASR_KEY, but the registry metadata lists no required env vars. Expect to provide an API key if you want cloud calls to work. Do not supply a high-privilege or unrelated credential; create a dedicated key with minimal scopes if possible. - Privacy: Using the cloud API uploads audio (and any reference audio used for voice-clone) to api.xiaomimimo.com. If audio contains sensitive or personal data, consider running the open-source local ASR model instead or avoid uploading sensitive recordings. - Voice cloning legality/consent: Voice-clone will upload reference audio (encoded in the request). Ensure you have consent to clone any person's voice. - Practical step: Inspect the included scripts (they are small and readable) and test the skill in a sandboxed environment with a throwaway API key or using local open-source models before enabling it for real data. If you need higher assurance, ask the publisher for a homepage or official vendor verification and request that required env vars be declared in the registry metadata.

Type: OpenClaw Skill Name: mimo-tts-asr Version: 2.5.4 The skill bundle provides legitimate Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) functionality via the Xiaomi MiMo API. The Python scripts (asr.py and tts.py) are well-structured API clients that use standard libraries (urllib) for network communication and include robust features like automatic retries, error handling, and argument validation. The documentation (SKILL.md) is comprehensive, providing clear usage examples and official resource links that align perfectly with the code's logic, with no evidence of malicious intent, obfuscation, or prompt injection.