sentiment-analyzer

Analyze video sentiment and emotion to produce sentiment scores, peaks, and timelines.

Updated Jan 30, 2026
One-click install
npx skills add https://github.com/akrindev/trimer-clip --skill sentiment-analyzer-akrindev
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sentiment-analyzer
Source: https://github.com/akrindev/trimer-clip/tree/main/skills/sentiment-analyzer
Command: npx skills add https://github.com/akrindev/trimer-clip --skill sentiment-analyzer-akrindev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Automatically identify emotional peaks and sentiment shifts in video content to inform highlight reels and storytelling decisions.

Core Features & Use Cases

  • Transcript-based keyword detection to derive emotional signals from transcripts and transcripts' text.
  • AI-based emotion analysis using Gemini API when GEMINI_API_KEY is available.
  • Audio-feature detection for non-transcript workflows.
  • Outputs include overall_sentiment, emotional_peaks, and sentiment_timeline for downstream editing tasks.
  • Integrates with other skills (e.g., highlight-scanner, video-trimmer) to build end-to-end sentiment-driven workflows.

Quick Start

Run the analyze_sentiment.py script on your video (and optional transcript) to generate a JSON report of sentiment, peaks, and timelines.

Frequently Asked Questions about sentiment-analyzer

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

FAQPage Schema
How do I analyze sentiment and emotion in video content?▼

You can analyze sentiment in video content by running the analyze_sentiment.py script on your video and optional transcript to generate a JSON report containing an overall sentiment score, emotional peaks, and a sentiment timeline.

Do I need a Gemini API key to detect emotion in a video transcript?▼

You do not need a Gemini API key to detect emotion in a video transcript. The tool defaults to transcript-based keyword detection and audio-feature analysis for non-transcript workflows, applying Gemini AI only when the GEMINI_API_KEY is available.

Can I identify emotional peaks in video content without a transcript?▼

You can identify emotional peaks in video content without a transcript using the built-in audio-feature detection mechanism, which extracts audio signals to evaluate sentiment shifts and generate a timeline for non-transcript scenarios.

What is the best way to track sentiment shifts over time for highlight reels?▼

The best way to track sentiment shifts over time for highlight reels is to generate a structured sentiment_timeline and emotional_peaks JSON output, which pinpoints exact moments of emotional intensity to inform downstream editing decisions.

Does the sentiment analyzer output integrate with video trimming tools?▼

The sentiment analyzer output integrates with video trimming and highlight scanning tools by exporting structured JSON results, allowing you to build end-to-end sentiment-driven workflows that automatically isolate emotional peaks for editing.