What transcript formats does the Meeting Insights Analyzer support?

The skill can scan and analyze various text-based formats including .txt, .md, .vtt, .srt, and .docx files commonly exported from Zoom, Google Meet, or Otter.ai.

Do I need to label speakers in my transcripts?

The analysis is most effective when transcripts include speaker labels, as this allows the skill to accurately calculate speaking ratios and isolate specific behavioral patterns for the user.

Can I use this for team coaching instead of personal analysis?

Yes, you can point the skill to a folder containing team transcripts to evaluate facilitation styles, participation balance, and how effectively the group reaches decisions.

How does the skill identify conflict avoidance?

It searches for specific linguistic markers such as hedging language ('potentially', 'maybe'), indirect phrasing, and moments where the user changes the subject during high-tension exchanges.

Meeting Insights Analyzer

Name: Meeting Insights Analyzer
Author: Krosebrook

byKrosebrook

•

协作工具

Analyzes meeting transcripts to identify behavioral patterns, communication habits, and actionable growth opportunities for professionals.

关于

The Meeting Insights Analyzer is a specialized Claude Code skill designed to transform raw meeting transcripts into a roadmap for professional development. By scanning for specific markers like conflict avoidance, speaking-to-listening ratios, and the use of filler words, it provides timestamped feedback on communication effectiveness. Whether you are looking to improve leadership facilitation, prepare for performance reviews, or coach team members, this tool helps uncover subtle behavioral trends that often go unnoticed in the heat of a conversation, turning verbal data into a structured personal growth plan.

主要功能

Detects frequent use of filler words and hedging language like 'maybe' or 'kind of'
Calculates precise speaking ratios, turn-taking dynamics, and interruption counts
Identifies recurring behavioral patterns such as conflict avoidance and indirect communication
Extracts timestamped examples of active listening, questioning, and facilitation moments
Generates longitudinal summaries to track communication improvements across multiple months
1 GitHub stars

使用场景

Coaching leaders and managers to improve their team facilitation and inclusive communication
Preparing evidence-based examples of communication growth for performance reviews
Analyzing client discovery calls to identify missed opportunities for direct questioning

关于

主要功能

Detects frequent use of filler words and hedging language like 'maybe' or 'kind of'
Calculates precise speaking ratios, turn-taking dynamics, and interruption counts
Identifies recurring behavioral patterns such as conflict avoidance and indirect communication
Extracts timestamped examples of active listening, questioning, and facilitation moments
Generates longitudinal summaries to track communication improvements across multiple months
1 GitHub stars

使用场景

Coaching leaders and managers to improve their team facilitation and inclusive communication
Preparing evidence-based examples of communication growth for performance reviews
Analyzing client discovery calls to identify missed opportunities for direct questioning