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naitynaity/professional-growth-agent/.claude/skills/meeting-transcription/SKILL.md

Meeting Transcription

Skill0 starsChanged 10 months agoMITView on GitHub

Transcribe audio recordings from meetings (MP3, WAV, M4A) into text using AWS Transcribe service

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use this skill when the user:

    line 12
  2. Distinctive:

    All transcriptions include speaker labels (spk_0, spk_1, spk_2, etc.) to identify different speakers in the conversation.

    line 52
  3. Very specific:

    When the user says: "Analyze my 1:1 meeting recording at ./recordings/meeting.mp3"

    line 66
  4. Distinctive:

    Use this skill to transcribe the audio first

    line 68
  5. Distinctive:

    After getting the transcript, analyze it for:

    line 74

≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Meeting Transcription Skill

This skill enables transcription of meeting audio files to text using AWS Transcribe.

When to Use This Skill

Use this skill when the user:

  • Provides an audio recording of a meeting
  • Asks to transcribe a meeting
  • Wants to analyze meeting content from an audio file
  • Mentions audio files with extensions like .mp3, .wav, .m4a, .mp4, .flac

How It Works

  1. User provides path to an audio file
  2. This skill calls the transcribe_audio.py script with optional language parameter
  3. The script uploads audio to S3 and uses AWS Transcribe
  4. Returns the full transcript as plain text with speaker labels (if applicable)
  5. You (the agent) can then analyze the transcript

Usage

IMPORTANT: Always specify the language to get speaker labels (spk_0, spk_1).

# English meeting (default)
python transcribe_audio.py /path/to/audio.mp3

# Chinese meeting
python transcribe_audio.py /path/to/audio.mp3 --language zh-CN

# Other languages
python transcribe_audio.py /path/to/audio.mp3 --language es-ES

Supported Languages:

  • en-US: English (US) - default
  • zh-CN: Mandarin Chinese (Simplified)
  • zh-TW: Traditional Chinese (Taiwan)
  • es-ES: Spanish (Spain)
  • fr-FR: French
  • de-DE: German
  • ja-JP: Japanese
  • ko-KR: Korean

Speaker Labels: All transcriptions include speaker labels (spk_0, spk_1, spk_2, etc.) to identify different speakers in the conversation. You must know the language beforehand.

Supported Audio Formats

  • MP3
  • MP4
  • WAV
  • FLAC
  • M4A
  • OGG
  • WebM

Usage Example

When the user says: "Analyze my 1:1 meeting recording at ./recordings/meeting.mp3"

  1. Use this skill to transcribe the audio first
  2. Once you have the transcript, analyze it for insights
  3. Provide actionable feedback to the user

What to Do After Transcription

After getting the transcript, analyze it for:

  • Key discussion topics: What were the main themes?
  • Action items: What tasks were assigned or agreed upon?
  • Speaking balance: Who spoke more? Is it balanced?
  • Questions: What questions were asked? Were they answered?
  • Communication patterns: Any interruptions, pauses, or unclear moments?
  • Tone and engagement: Is the conversation collaborative or one-sided?
  • Constructive feedback: What could be improved for next time?

Technical Details

  • Requires AWS credentials configured
  • Requires S3 bucket for temporary audio storage
  • Audio files are automatically cleaned up after transcription
  • Transcription job names are timestamped to avoid conflicts

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