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sentiment-analyzer

sentiment-analyzer

github.com/guia-matthieuData & databases150217 installsUpdated 4w ago
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About sentiment-analyzer

sentiment-analyzer is a command-line skill for analyzing customer text with transformer models or lighter CPU-only alternatives. It supports single-text and CSV batch analysis, plus HTML reports for feedback and review workflows.

Key features

  1. 01Analyzes sentiment in text
  2. 02Processes CSV batches
  3. 03Generates HTML reports
  4. 04Supports transformer and CPU-only options

Use cases

  1. 01Categorize product reviews
  2. 02Analyze open-ended NPS responses
  3. 03Review support ticket sentiment
  4. 04Evaluate campaign feedback

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/guia-matthieu/clawfu-skills --skill sentiment-analyzer

After installing, type/sentiment-analyzerin Claude Code to confirm it loaded.

Bundled filesscripts/main.pyscripts/requirements.txt

Details

From the project README

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

Analyze Text
python scripts/main.py analyze "This product exceeded my expectations!"
python scripts/main.py analyze "The service was terrible and slow."
Batch Analysis
python scripts/main.py batch reviews.csv --column text
python scripts/main.py batch feedback.csv --column comment --output results.csv
Generate Report
python scripts/main.py report reviews.csv --column text --output sentiment-report.html

Examples

Example 1: Analyze Product Reviews
# Process CSV of reviews
python scripts/main.py batch amazon-reviews.csv --column review_text

# Output: amazon-reviews_sentiment.csv
# review_text                    | sentiment | score  | label
# "Absolutely love this!"        | positive  | 0.95   | Very Positive
# "It's okay, nothing special"   | neutral   | 0.52   | Neutral
# "Worst purchase ever"          | negative  | 0.12   | Very Negative
Example 2: NPS Feedback Categorization
# Analyze NPS survey responses
python scripts/main.py report nps-responses.csv --column feedback

# Output: sentiment-report.html
# Summary:
# - Positive: 62% (mainly: product quality, support)
# - Neutral: 23% (mainly: pricing concerns)
# - Negative: 15% (mainly: shipping delays)

Sentiment Categories

Score RangeLabelInterpretation
0.8 - 1.0Very PositiveEnthusiastic, recommend
0.6 - 0.8PositiveSatisfied, happy
0.4 - 0.6NeutralMixed or indifferent
0.2 - 0.4NegativeDisappointed, frustrated
0.0 - 0.2Very NegativeAngry, will churn

Skill Boundaries

What This Skill Does Well
  • Structuring data analysis
  • Identifying patterns and trends
  • Creating visualization frameworks
  • Calculating statistical measures
What This Skill Cannot Do
  • Access your actual data
  • Replace statistical expertise
  • Make business decisions
  • Guarantee prediction accuracy

Related Skills

Skill Metadata

  • Mode: centaur
category: analytics
subcategory: nlp
dependencies: [transformers, torch, pandas]
difficulty: intermediate
time_saved: 6+ hours/week

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