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Sentiment Analyzer

This one's for processing customer feedback at scale without burning hours on manual categorization. It runs transformer models locally to analyze sentiment in reviews, NPS responses, or support tickets, giving you scored outputs from very positive to very negative. The batch processing handles CSVs and generates HTML reports with breakdown summaries. ClawFu built it with both heavy ML and lighter CPU options depending on your setup. Honestly most useful when you've got hundreds of text entries to sort through and need to spot patterns fast. The categorization table showing score ranges is helpful for setting up automations or dashboards based on sentiment thresholds.

skills.sh installs
221
GitHub stars
150
last updated
Aug 21, 2026

Install

$ npx -y skills add guia-matthieu/clawfu-skills --skill sentiment-analyzer --agent claude-code

Installs into .claude/skills of the current project.

Files

Sentiment Analyzer

Analyze sentiment in customer feedback using transformer models - understand what your customers really feel at scale.

When to Use This Skill

  • Review analysis - Process hundreds of product reviews
  • NPS feedback - Categorize open-ended survey responses
  • Social listening - Monitor brand sentiment on social media
  • Campaign feedback - Evaluate response to marketing campaigns
  • Support insights - Categorize support ticket sentiment

What Claude Does vs What You Decide

Claude DoesYou Decide
Structures analysis frameworksMetric definitions
Identifies patterns in dataBusiness interpretation
Creates visualization templatesDashboard design
Suggests optimization areasAction priorities
Calculates statistical measuresDecision thresholds

Dependencies

pip install transformers torch pandas click
# Or for lighter CPU-only version:
pip install textblob vaderSentiment pandas click

Commands

Sponsors

Details

Repository
github.com/guia-matthieu/clawfu-skills
Categories
DevOps & CI/CD, Data Science & ML, Marketing & SEO
First seen
Jun 3, 2026

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