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voice-analyzer

Analyze community posts for sentiment, attitudes, features, and quotes.

1|Updated Mar 5, 2026
Search Tags:#sentiment analysis#community insights#feature extraction#user feedback#voice of customer#attitude tagging
One-click install
npx skills add https://github.com/anserIndicus/community-research-skills --skill voice-analyzer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: voice-analyzer
Source: https://github.com/anserIndicus/community-research-skills/tree/main/voice-analyzer
Command: npx skills add https://github.com/anserIndicus/community-research-skills --skill voice-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms unstructured community posts and comments into structured, quantifiable data, revealing user emotions, attitudes, and specific needs.

Core Features & Use Cases

  • Sentiment Analysis: Understand the emotional tone (positive, negative, neutral) of user feedback.
  • Attitude Tagging: Categorize user attitudes like complaining, requesting, or recommending.
  • Feature Mention Extraction: Identify specific product features users are discussing.
  • Use Case: Analyze thousands of app reviews to pinpoint the most common pain points and feature requests, informing your product roadmap.

Quick Start

Analyze the sentiment and key features mentioned in the provided user feedback data.

Frequently Asked Questions about voice-analyzer

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

FAQPage Schema
How do I extract feature mentions and sentiment from user feedback?▼

To extract feature mentions and sentiment from user feedback, this Skill applies multi-dimensional structured analysis on cleaned community posts to categorize emotional polarity, tag attitudes, and identify specific product features discussed.

What is the best way to tag user attitudes like complaining or requesting in community posts?▼

Tagging user attitudes in community posts is achieved through attitude tagging, which categorizes user feedback into specific behavioral intents like complaining, requesting, or recommending based on the extracted text context.

Can I use sentiment analysis on app reviews to inform a product roadmap?▼

Sentiment analysis can be used on app reviews to pinpoint common pain points and feature requests, transforming unstructured comments into quantifiable data to directly inform your product roadmap decisions.

How do I pull high-value quotes from community comments for experience scenarios?▼

Pulling high-value quotes from community comments involves processing user feedback to extract experience scenarios, isolating impactful statements that reveal specific user demands and emotional contexts.

Do I need cleaned community posts to perform voice of customer analysis?▼

Yes, you need cleaned community posts because the analysis engine requires pre-processed text to accurately perform sentiment polarity detection, attitude tagging, and feature extraction without raw data noise.

How does voice of customer analysis handle unstructured product feedback?▼

Voice of customer analysis handles unstructured product feedback by performing comprehensive structured analysis, transforming raw community comments into quantifiable data that reveals user emotions, attitudes, and specific needs.

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