Is my meeting data private when using this skill?

Yes, the analysis is performed through Claude Code within your local environment, ensuring that sensitive meeting content is handled according to your existing security configuration.

Does this skill require speaker labels in the transcripts?

While it can analyze general tone, it is most effective when transcripts include speaker labels so it can accurately attribute specific patterns and statistics to you.

What file types does the Meeting Insights Analyzer support?

The skill can process a variety of transcript formats including .txt, .md, .vtt, .srt, and .docx files provided they are stored in a folder accessible to Claude Code.

Can it track my communication progress over time?

Yes, by analyzing folders containing meetings from different dates, the skill can generate comparative summaries to show how your speaking ratios or use of filler words have changed.

How do I provide transcripts to the skill?

You can export transcripts from platforms like Zoom, Google Meet, Granola, or Fireflies and save them into a dedicated folder. Claude Code then scans this folder to perform the analysis.

Meeting Insights Analyzer

Name: Meeting Insights Analyzer
Author: prof-ramos

byprof-ramos

•

コラボレーションツール

Analyzes meeting transcripts to identify communication patterns, behavioral habits, and actionable leadership feedback.

概要

The Meeting Insights Analyzer is a specialized skill for Claude Code designed to turn raw meeting transcripts into a powerful tool for professional development. By scanning transcript files for subtle patterns such as conflict avoidance, hedging language, and speaking-to-listening ratios, it provides users with timestamped examples and data-driven recommendations. Whether you are looking to refine your facilitation style, eliminate filler words, or track your growth as a communicator over time, this skill offers the objective analysis needed to enhance your executive presence and team collaboration.

主な機能

Pattern recognition for conflict avoidance and indirect communication
1 GitHub stars
Comparative trend analysis across multiple meeting sessions
Automated detection of filler words and hedging language
Timestamped feedback with specific alternative phrasing suggestions
Detailed speaking statistics including talk-time ratios and interruption counts

ユースケース

Identifying and correcting indirect communication habits in high-stakes meetings
Preparing for performance reviews with concrete data on communication improvements
Improving leadership facilitation by monitoring inclusivity and active listening

概要

主な機能

Pattern recognition for conflict avoidance and indirect communication
1 GitHub stars
Comparative trend analysis across multiple meeting sessions
Automated detection of filler words and hedging language
Timestamped feedback with specific alternative phrasing suggestions
Detailed speaking statistics including talk-time ratios and interruption counts

ユースケース

Identifying and correcting indirect communication habits in high-stakes meetings
Preparing for performance reviews with concrete data on communication improvements
Improving leadership facilitation by monitoring inclusivity and active listening