{ "name": "@tpmjs/feedback-themes", "version": "0.1.0", "description": "Extracts themes and sentiment from customer feedback text", "type": "module", "keywords": [ "tpmjs", "cx", "feedback", "sentiment", "analysis", "customer-success" ], "exports": { ".": { "types": "./dist/index.d.ts", "default": "./dist/index.js" } }, "files": [ "dist" ], "scripts": { "build": "tsup", "dev": "tsup --watch", "type-check": "tsc --noEmit", "clean": "rm -rf dist .turbo" }, "devDependencies": { "@tpmjs/tsconfig": "workspace:*", "tsup": "^8.5.1", "typescript": "^5.9.3" }, "publishConfig": { "access": "public" }, "repository": { "type": "git", "url": "https://github.com/ajaxdavis/tpmjs.git", "directory": "packages/tools/official/feedback-themes" }, "homepage": "https://tpmjs.com", "license": "MIT", "tpmjs": { "category": "cx", "frameworks": [ "vercel-ai" ], "tools": [ { "name": "feedbackThemesTool", "description": "Extracts themes and sentiment from customer feedback text. Identifies recurring themes, scores sentiment per theme, and provides frequency counts.", "parameters": [ { "name": "feedback", "type": "string[]", "description": "Array of customer feedback entries", "required": true } ], "returns": { "type": "FeedbackThemes", "description": "Themes with sentiment scores, frequency counts, and example feedback" }, "aiAgent": { "useCase": "Use this tool to analyze customer feedback, identify common themes, track sentiment trends, and prioritize product improvements based on customer voice.", "limitations": "Sentiment analysis is keyword-based. For complex sentiment, consider using an AI model. Requires sufficient feedback volume for meaningful themes.", "examples": [ "Analyze product reviews to identify improvement areas", "Extract themes from NPS survey comments", "Track sentiment trends across feedback channels" ] } } ] }, "dependencies": { "ai": "6.0.23" } }