Feedback Analyzer
Analyzes user feedback to identify key themes and sentiment, offering valuable insights for product improvement and customer understanding.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add feedback-analyzer npx -- -y @trustedskills/feedback-analyzer
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"feedback-analyzer": {
"command": "npx",
"args": [
"-y",
"@trustedskills/feedback-analyzer"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The Feedback Analyzer skill processes user input to extract and categorize specific feedback data. It helps AI agents understand sentiment, identify key topics, and summarize actionable insights from raw text.
When to use it
- Reviewing customer support tickets to detect recurring complaints.
- Analyzing open-ended survey responses for qualitative trends.
- Summarizing meeting transcripts to highlight team suggestions or concerns.
- Evaluating code pull requests for constructive criticism and praise.
Key capabilities
- Sentiment detection within text blocks.
- Topic extraction and categorization.
- Structured summarization of unstructured feedback.
- Actionable insight generation based on input analysis.
Example prompts
- "Analyze these 50 customer reviews and summarize the top three positive themes."
- "Extract all negative feedback regarding the new login feature from this dataset."
- "Categorize the following survey responses by sentiment and provide a brief summary for each category."
Tips & gotchas
Ensure input text is clean and free of excessive noise, as raw data quality directly impacts analysis accuracy. For best results, specify the desired output format (e.g., JSON, bullet points) in your prompt to match downstream workflow requirements.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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Passed automated security scans.