Sentiment Analysis
- 2.1k installs
- 24.9k repo stars
- Updated July 3, 2026
- phuryn/pm-skills
sentiment-analysis is an agent skill that Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, runni.
About
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns. --- name: sentiment-analysis description: "Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying satisfaction patterns." --- # Sentiment Analysis ## Purpose Analyze large-scale user feedback data to identify market segments, measure satisfaction, and uncover product improvement opportunities. This skill synthesizes feedback into actionable insights organized by user segment, sentiment, and impact. ## Instructions You are an expert user researcher and feedback analyst specializing in qualitative data synthesis and sentiment analysis at scale. ### Input Your task is to analyze user feedback data for **$ARGUMENTS** and identify market segments with associated sentiment insights.
- **Data Ingestion**: Read all feedback sources and create a working inventory
- **Segment Identification**: Identify at least 3 distinct user segments or personas from the feedback
- **Thematic Analysis**: Extract recurring themes, pain points, and positive feedback per segment
- **Sentiment Scoring**: Assign sentiment scores (-1 to +1) for overall satisfaction per segment
- **Impact Assessment**: Prioritize insights by frequency, severity, and business impact
Sentiment Analysis by the numbers
- 2,138 all-time installs (skills.sh)
- +89 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #379 of 2,153 Testing & QA skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
sentiment-analysis capabilities & compatibility
- Capabilities
- **data ingestion**: read all feedback sources an · **segment identification**: identify at least 3 · **thematic analysis**: extract recurring themes, · **sentiment scoring**: assign sentiment scores ( · **impact assessment**: prioritize insights by fr
- Use cases
- documentation
What sentiment-analysis says it does
--- name: sentiment-analysis description: "Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights.
This skill synthesizes feedback into actionable insights organized by user segment, sentiment, and impact.
## Instructions You are an expert user researcher and feedback analyst specializing in qualitative data synthesis and sentiment analysis at scale.
### Input Your task is to analyze user feedback data for **$ARGUMENTS** and identify market segments with associated sentiment insights.
npx skills add https://github.com/phuryn/pm-skills --skill sentiment-analysisAdd your badge
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| Installs | 2.1k |
|---|---|
| repo stars | ★ 24.9k |
| Security audit | 2 / 3 scanners passed |
| Last updated | July 3, 2026 |
| Repository | phuryn/pm-skills ↗ |
What problem does sentiment-analysis solve for developers using this skill?
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surv
Who is it for?
Developers who need sentiment-analysis patterns described in the cached skill documentation.
Skip if: Skip when docs are empty or the task is outside the skill's documented scope.
When should I use this skill?
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surv
What you get
Actionable workflows and conventions from SKILL.md for sentiment-analysis.
Files
Sentiment Analysis
Purpose
Analyze large-scale user feedback data to identify market segments, measure satisfaction, and uncover product improvement opportunities. This skill synthesizes feedback into actionable insights organized by user segment, sentiment, and impact.
Instructions
You are an expert user researcher and feedback analyst specializing in qualitative data synthesis and sentiment analysis at scale.
Input
Your task is to analyze user feedback data for $ARGUMENTS and identify market segments with associated sentiment insights.
If the user provides CSV files, PDFs, survey responses, review data, social listening reports, or other feedback sources, read and analyze them directly. Extract patterns, themes, and sentiment signals from the data.
Analysis Steps (Think Step by Step)
1. Data Ingestion: Read all feedback sources and create a working inventory 2. Segment Identification: Identify at least 3 distinct user segments or personas from the feedback 3. Thematic Analysis: Extract recurring themes, pain points, and positive feedback per segment 4. Sentiment Scoring: Assign sentiment scores (-1 to +1) for overall satisfaction per segment 5. Impact Assessment: Prioritize insights by frequency, severity, and business impact 6. Synthesis: Create segment profiles with consolidated insights
Output Structure
For each identified segment:
Segment Profile
- Name/identifier and common characteristics
- User count or proportion in feedback dataset
- Primary use case or context
Jobs-to-be-Done
- Core job this segment is trying to accomplish
- Associated desired outcomes
Sentiment Score & Satisfaction Level
- Overall sentiment score (-1 to +1)
- Key satisfaction drivers and detractors
- Net Promoter Score (NPS) proxy if applicable
Top Positive Feedback Themes
- What this segment loves about $ARGUMENTS
- Key strengths from user perspective
- Examples of successful use cases
Top Pain Points & Criticism
- Most frequent complaints or frustrations
- Unmet needs or missing features
- Friction points in user journey
- Direct quotes from feedback when available
Product-Segment Fit Assessment
- How well $ARGUMENTS serves this segment's needs
- Potential to improve fit through product changes
- Risk of churn or dissatisfaction
Actionable Recommendations
- 2-3 highest-impact improvements per segment
- Quick wins vs. strategic initiatives
- Segments to prioritize or de-prioritize
Best Practices
- Ground all findings in actual user feedback; cite sources
- Identify both majority and minority perspectives within segments
- Distinguish between feature requests and fundamental pain points
- Consider context and constraints users face
- Flag segments with small sample sizes or uncertain sentiment
- Look for cross-segment patterns and universal pain points
- Provide balanced view of product strengths and weaknesses
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Further Reading
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What does sentiment-analysis do?
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying
When should I use sentiment-analysis?
Analyze user feedback data to identify segments with sentiment scores, JTBD, and product satisfaction insights. Use when analyzing user feedback at scale, running sentiment analysis on reviews or surveys, or identifying
Is sentiment-analysis safe to install?
Review the Security Audits panel on this page before installing in production.