Execute this skill enables AI assistant to analyze the sentiment of text data. it identifies the emotional tone expressed in text, classifying it as positive, negative, or neutral. use this skill when a user requests sentiment analysis, opinion mining, or emoti... Use when analyzing code or data. Trigger with phrases like 'analyze', 'review', or 'examine'.
Analyzes text to identify emotional tone and classify it as positive, negative, or neutral. Activates when users request sentiment analysis, opinion mining, or emotional tone assessment of reviews, social media, or feedback.
/plugin marketplace add jeremylongshore/claude-code-plugins-plus/plugin install sentiment-analysis-tool@claude-code-plugins-plusThis skill is limited to using the following tools:
assets/README.mdassets/sentiment_analysis_report_template.mdreferences/README.mdscripts/README.mdscripts/analyze_sentiment.pyscripts/example_usage.pyThis skill provides automated assistance for sentiment analysis tool tasks.
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.
This skill activates when you need to:
User request: "Analyze the sentiment of these customer reviews: 'The product is amazing!', 'The service was terrible.', 'It was okay.'"
The skill will:
User request: "Perform sentiment analysis on the following tweet: 'I love this new feature!'"
The skill will:
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).
The skill produces structured output relevant to the task.
Use when working with Payload CMS projects (payload.config.ts, collections, fields, hooks, access control, Payload API). Use when debugging validation errors, security issues, relationship queries, transactions, or hook behavior.