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kalilurrahman
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feedback-analyzer

Classify raw user feedback into themes, sentiment, urgency, and actionable recommendations.

1|Updated Mar 21, 2026
Search Tags:#product management#classification#themes#csv#sentiment#user insights#feedback analysis
One-click install
npx skills add https://github.com/kalilurrahman/kr-claudiator-skills-original-prompts --skill feedback-analyzer-kalilurrahman
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: feedback-analyzer
Source: https://github.com/kalilurrahman/kr-claudiator-skills-original-prompts/tree/main/09-product-management/feedback-analyzer
Command: npx skills add https://github.com/kalilurrahman/kr-claudiator-skills-original-prompts --skill feedback-analyzer-kalilurrahman

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Product teams receive messy, unstructured user feedback from many sources and struggle to turn it into prioritized decisions. This Skill converts pasted text or CSV feedback dumps into structured themes, sentiment distributions, and concrete PM recommendations. ## Core Features & Use Cases - Feedback Classification: Assigns each entry a theme, sentiment, urgency level, and type (bug report, feature request, complaint, praise, question). - Pattern Aggregation: Counts themes, calculates sentiment distribution, and surfaces non-obvious correlations such as churn risk or expansion signals. - Prioritized Recommendations: Produces a P0/P1/P2 action table with expected impact, backed by verbatim user quotes. - Use Case: Paste 200 support tickets or point to a CSV of NPS comments, and receive a themes table, top 3 patterns, and a prioritized action list for your next sprint planning. ## Quick Start Analyze the user feedback in feedback-export.csv and give me the top themes, sentiment breakdown, and recommended actions.

Frequently Asked Questions about feedback-analyzer

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

FAQPage Schema
How do I analyze user feedback for product insights?▼

Paste raw feedback text or provide a path to a CSV file. Each entry is classified by theme, sentiment, urgency, and type, then aggregated into a themes table, top patterns, and prioritized recommendations for product decisions.

How to categorize customer feedback into themes automatically?▼

Each feedback entry is assigned a dominant theme such as Onboarding, Pricing, or Performance, with secondary themes noted when relevant. A minimum of three themes is enforced, and single-theme results are split into sub-themes.

Can I analyze feedback from a CSV file?▼

Yes, provide a file path and the CSV is parsed using command-line tools like csvtool, awk, or Python. Pasted plain text also works, split by line or paragraph into individual entries.

What is the minimum amount of feedback needed for analysis?▼

At least 5 entries are required to draw conclusions. With fewer entries, the analysis explicitly flags weak signals and states that the volume is too small for reliable patterns.

How is feedback urgency determined?▼

Urgency is based on language intensity and frequency, not subjective judgment. Words like broken, can't use, or blocking indicate High urgency, while milder phrasing maps to Medium or Low.

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