analyzing-text-sentiment
Classify text as positive, negative, or neutral with confidence scores.
Install
mkdir -p .claude/skills/analyzing-text-sentiment && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4775" && unzip -o skill.zip -d .claude/skills/analyzing-text-sentiment && rm skill.zipInstalls to .claude/skills/analyzing-text-sentiment
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Execute this skill enables AI assistant to analyze the sentiment ofKey capabilities
- →Classify text sentiment as positive, negative, or neutral
- →Calculate sentiment confidence scores
- →Analyze customer reviews and survey responses
- →Monitor social media post emotional tone
How it works
The skill processes input text through a pre-trained sentiment analysis model to determine polarity. It then returns a structured classification and score.
Inputs & outputs
When to use analyzing-text-sentiment
- →Determine sentiment of customer reviews
- →Analyze emotional tone of social media posts
- →Gauge public opinion on topics
- →Identify positive or negative feedback trends
About this skill
Sentiment Analysis Tool
Classify text sentiment as positive, negative, or neutral with confidence scores for customer reviews, social media posts, and survey responses.
Overview
This skill empowers Claude to perform sentiment analysis on text, providing insights into the emotional content and polarity of the provided data. By leveraging AI/ML techniques, it helps understand public opinion, customer feedback, and overall emotional tone in written communication.
How It Works
- Text Input: The skill receives text data as input from the user.
- Sentiment Analysis: The skill processes the text using a pre-trained sentiment analysis model to determine the sentiment polarity (positive, negative, or neutral).
- Result Output: The skill provides a sentiment score and classification, indicating the overall sentiment expressed in the text.
When to Use This Skill
This skill activates when you need to:
- Determine the overall sentiment of customer reviews.
- Analyze the emotional tone of social media posts.
- Gauge public opinion on a particular topic.
- Identify positive and negative feedback in survey responses.
Examples
Example 1: Analyzing Customer Reviews
User request: "Analyze the sentiment of these customer reviews: 'The product is amazing!', 'The service was terrible.', 'It was okay.'"
The skill will:
- Process the provided customer reviews.
- Classify each review as positive, negative, or neutral and provide sentiment scores.
Example 2: Monitoring Social Media Sentiment
User request: "Perform sentiment analysis on the following tweet: 'I love this new feature!'"
The skill will:
- Analyze the provided tweet.
- Identify the sentiment as positive and provide a corresponding sentiment score.
Best Practices
- Data Quality: Ensure the input text is clear and free from ambiguous language for accurate sentiment analysis.
- Context Awareness: Consider the context of the text when interpreting sentiment scores, as sarcasm or irony can affect results.
- Model Selection: Use appropriate sentiment analysis models based on the type of text being analyzed (e.g., social media, customer reviews).
Integration
This skill can be integrated with other Claude Code plugins to automate workflows, such as summarizing feedback alongside sentiment scores or triggering actions based on sentiment polarity (e.g., escalating negative feedback).
Prerequisites
- Appropriate file access permissions
- Required dependencies installed
Instructions
- Invoke this skill when the trigger conditions are met
- Provide necessary context and parameters
- Review the generated output
- Apply modifications as needed
Output
The skill produces structured output relevant to the task.
Error Handling
- Invalid input: Prompts for correction
- Missing dependencies: Lists required components
- Permission errors: Suggests remediation steps
Resources
- Project documentation
- Related skills and commands
When not to use it
- →Analyzing text containing heavy sarcasm or irony
- →Processing ambiguous language without clear context
Prerequisites
Limitations
- →Accuracy depends on input text clarity
- →Sarcasm and irony can affect sentiment score interpretation
How it compares
This skill automates the classification of emotional tone using machine learning rather than manual review of text data.
Compared to similar skills
analyzing-text-sentiment side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| analyzing-text-sentiment (this skill) | 1 | 26d | Review | Beginner |
| quant-analyst | 103 | 2mo | No flags | Advanced |
| umap-learn | 6 | 2mo | Review | Intermediate |
| embedding-strategies | 8 | 2mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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