Meeting Recorder Assistant

Intelligent meeting recording and transcription assistant with automated minutes generation, action item extraction, and sentiment analysis. Supports audio t...

This package contains plausible meeting-recording code but also some red flags you should consider before installing or running it: - Feature mismatch: The description advertises speaker diarization and sentiment analysis, but the included Python files do not implement those features. Expect only basic recording, Google-based transcription, and regex-based minutes/action extraction. - Unexpected dependency: requirements.txt lists openai even though none of the code uses it. That implies either leftover/unnecessary dependencies or hidden/unused code paths. Review and remove unused packages before installing to limit attack surface. - External network/privacy: The transcription uses speech_recognition.recognize_google(), which sends audio to a Google speech API endpoint. If you will process sensitive audio, treat this as data exfiltration to an external service and get consent from participants or run a local/offline recognizer. - Native deps and permissions: pyaudio requires platform native libraries and microphone access. Installing and running this skill may require elevated packaging steps and will access your microphone when recording; run in a controlled environment. - Sanity checks to perform: inspect and/or remove the openai dependency; run the code in a disposable virtual environment; audit for any network calls (use network monitoring during a test run); confirm where transcripts are stored and that temporary paths (/tmp) are acceptable for your privacy requirements. Overall: the code itself is not overtly malicious, but the mismatch between advertised features and actual implementation plus the unnecessary dependency create enough incoherence to warrant caution.

Type: OpenClaw Skill Name: meeting-recorder-assistant Version: 1.0.0 The meeting-recorder-assistant skill bundle provides legitimate functionality for recording audio, transcribing speech to text, and generating meeting summaries. The implementation uses standard libraries such as SpeechRecognition and PyAudio for its core features, and the data extraction logic in scripts/meeting_minutes.py and scripts/action_extractor.py relies on simple regular expressions. No evidence of malicious intent, data exfiltration, or prompt injection was found across the code or documentation.