awesome-claude-skills

### Skill: Automated Meeting Notes Generator

**Purpose**: Automatically transcribes Zoom/Google Meet meetings, generates structured notes with action items, and shares them via Slack to the relevant team channel.

**Dependencies**:
- `pydub` (for audio processing)
- `speech_recognition` (for transcription)
- `slack_sdk` (for notifications)
- `google-api-python-client` (for Google Calendar integration)

**Implementation**:
1. Create a new Python file `meeting_notes_skill.py` in your Claude Skills directory.
2. Add the following code:
```python
import os
from pydub import AudioSegment
import speech_recognition as sr
from slack_sdk import WebClient
from google.oauth2.credentials import Credentials
from googleapiclient.discovery import build

def transcribe_audio(audio_path):
    recognizer = sr.Recognizer()
    audio = AudioSegment.from_mp3(audio_path)
    audio.export("temp.wav", format="wav")
    with sr.AudioFile("temp.wav") as source:
        audio_data = recognizer.record(source)
    return recognizer.recognize_google(audio_data)

def generate_notes(transcript):
    # Simple NLP processing to extract action items
    action_items = []
    for line in transcript.split('\n'):
        if any(word in line.lower() for word in ['action item', 'todo', 'next steps']):
            action_items.append(line)
    return {"transcript": transcript, "action_items": action_items}

def send_to_slack(notes, channel):
    client = WebClient(token=os.getenv('SLACK_TOKEN'))
    message = f"Meeting Notes:\n{notes['transcript']}\n\nAction Items:\n" + "\n".join(notes['action_items'])
    client.chat_postMessage(channel=channel, text=message)

# Example usage
if __name__ == "__main__":
    transcript = transcribe_audio("meeting_audio.mp3")
    notes = generate_notes(transcript)
    send_to_slack(notes, "#project-alpha")
```

**Example Workflow**:
1. User records a meeting in Zoom and saves the audio file to `~/meetings/`.
2. User runs: `claude run meeting_notes_skill.py --input ~/meetings/meeting_20240515.mp3 --channel #project-alpha`
3. Skill processes the audio, generates notes, and posts them to Slack with action items highlighted.

**Error Handling**:
- Add try/except blocks for API rate limits (Slack/Google).
- Implement retry logic for transcription failures.
- Log errors to `meeting_notes.log` for debugging.

**Testing**:
Run with test audio file: `claude test meeting_notes_skill.py`
Expected output: Structured notes in Slack channel with 90%+ accuracy for clear audio.