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Gemini Voice Assistant

v1.0.0

Voice-to-voice AI assistant using Gemini Live API. Speak to the AI and get spoken responses. Use when you want to have natural voice conversations with an AI...

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byAli Mostafa Radwan@alimostafaradwan
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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Purpose & Capability
The handler.py implements a Gemini Live audio/text client, depends on google-genai and audio libraries, and uses ffmpeg for conversion — which is coherent with a 'Gemini Voice Assistant'. However the registry metadata provided to the evaluator claimed 'Required env vars: none' while skill.json and the code require GEMINI_API_KEY. That metadata mismatch is an inconsistency you should resolve before trusting the package source.
Instruction Scope
SKILL.md instructions map directly to the CLI entrypoint in handler.py. The runtime reads a .env file in the skill directory (documented) and uses GEMINI_API_KEY from the environment; it writes temporary audio to /tmp and invokes ffmpeg. The instructions do not attempt to read unrelated system files or send data to endpoints other than the Gemini API.
Install Mechanism
There is no automated install spec (instruction-only behavior plus a Python script). Dependencies are standard Python packages and FFmpeg is expected to be present on the host. No external archive downloads or custom installers are present in the skill bundle.
Credentials
Requiring a single GEMINI_API_KEY is proportionate to contacting Gemini. The code will also load any key-value pairs from a local .env file into the process environment (only if present), so any secrets stored there may be read by the skill — ensure that .env contains only the intended API key. The earlier registry claim of 'no env vars' contradicts the code and skill.json, which is concerning.
Persistence & Privilege
The skill does not request always:true and does not modify other skills or global config. It does create audio files under /tmp and leaves OGG output there; this is local persistence but not an elevated platform privilege.
What to consider before installing
What to consider before installing: - Metadata mismatch: the registry metadata claims no required env vars, but skill.json and handler.py require GEMINI_API_KEY. Verify the source and ask the publisher to correct metadata before trusting the package. - Secrets: the skill will read a .env file in its directory and import values into the process environment if present. Do not put unrelated secrets in that .env file; only store the Gemini API key there if you accept the risk. - Network and privacy: the skill uses google-genai to connect to Google's Gemini service — any voice/text you send will go to Google's servers. If you have privacy concerns, do not use it with sensitive data. - Local files: the skill writes audio to /tmp/gemini_voice_<id>.ogg and removes an intermediate WAV file. OGG files may persist until cleared; consider automatic cleanup or a different output directory if multiple users share the system. - Dependencies and binaries: you must install the listed Python packages and ensure FFmpeg is available at the expected path (handler.py uses /usr/bin/ffmpeg). Confirm the google-genai package you install is the official one and review its network behavior. - Source trust: the skill has no homepage and an unknown source/owner. If you need strong assurance, request a verified source, a repository link, or an upstream release to inspect before running it with your API key. If those concerns are acceptable and you trust the publisher, the code itself is consistent with its stated functionality; otherwise treat this as untrusted until the metadata and provenance issues are resolved.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

Runtime requirements

🎙️ Clawdis

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