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transcript-analysis

Extract speaker-attributed quotes and action items from transcripts using SCQA.

29|12|Updated Mar 30, 2026
Search Tags:#transcript#summarization#analysis#insights#meetings#scqa
One-click install
npx skills add https://github.com/matteotitta/genesys-skills --skill transcript-analysis-matteotitta
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: transcript-analysis
Source: https://github.com/matteotitta/genesys-skills/tree/main/skills/primitives/social/youtube/transcripts
Command: npx skills add https://github.com/matteotitta/genesys-skills --skill transcript-analysis-matteotitta

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the challenge of extracting actionable, verifiable intelligence from long-form recordings like podcasts, webinars, and meetings without falling victim to AI hallucinations.

Core Features & Use Cases

  • Verifiable Insights: Every insight is anchored to a timestamped, speaker-attributed verbatim quote, ensuring total auditability.
  • SCQA Framework: Automatically structures raw transcript data into the Situation-Complication-Question-Answer format for high-impact communication.
  • Use Case: Use this to process a 60-minute industry webinar into a structured report containing key themes, prioritized action items, and specific proof points for your content strategy.

Quick Start

Analyze the transcript from the provided video URL and extract the key themes and action items using the transcript-analysis skill.

Frequently Asked Questions about transcript-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract structured insights from long-form meeting transcripts?▼

To extract structured insights from meeting transcripts, apply the SCQA framework to map speaker-attributed quotes and timestamps, generating prioritized action items while maintaining strict anti-hallucination guardrails for data auditability.

What is the SCQA framework for transcript summarization?▼

The SCQA framework for transcript summarization structures raw transcript data into Situation, Complication, Question, and Answer formats, enabling high-impact communication and verifiable intelligence extraction from long-form audio recordings.

How do I prevent AI hallucinations when analyzing podcast transcripts?▼

Prevent AI hallucinations during podcast transcript analysis by enforcing strict guardrails that anchor every insight to a timestamped, speaker-attributed verbatim quote, ensuring total auditability and data integrity.

Can I generate speaker-attributed action items from a webinar recording?▼

Yes, you can generate speaker-attributed action items from a webinar recording by processing the transcript with consistent speaker identification and timestamp mapping to extract prioritized, verifiable tasks.

Does transcript analysis work without consistent speaker identification?▼

No, transcript analysis requires consistent speaker identification and timestamp mapping to ensure data integrity, properly attribute verbatim quotes, and maintain the auditability of extracted insights.

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