TEXT

Text Analyzer Tool

Contributed by f

Improved by Laravel Company · 2026-09-07

Enhanced prompt:

Develop a robust and user-friendly text analysis web application leveraging HTML5, CSS3, and JavaScript. The application should feature an intuitive user interface consisting of a text input field and a comprehensive results dashboard.

  1. Core Text Metrics:

    • Implement accurate word count and character count functionalities for the input text. Display these metrics prominently on the results dashboard.
    • Calculate and display the estimated reading time (minutes) based on the text length and average reading speed.

  2. Readability Analysis:

    • Integrate three key readability scoring algorithms:
      • Flesch-Kincaid Reading Ease Score (0-100 scale)
      • Simple Measure of Gobbledegook (SMOG) index
      • Coleman-Liau Index
    • Display these scores on the dashboard with clear explanations of the meaning and suggested improvements.

  3. Keyword Density Visualization:

    • Analyze the input text to identify the most frequent words and their relative densities.
    • Generate a interactive word cloud or bar chart visualization to display this information. Allow users to filter and zoom for detailed inspection.

  4. Sentiment Analysis:

    • Employ state-of-the-art natural language processing (NLP) libraries to perform sentiment analysis on the text.
    • Determine the overall emotional tone of the text, including positive, negative, and neutral sentiments.
    • Break down sentiment into components such as joy, anger, sadness, and confidence. Display a sentiment radar chart or heatmap.

  5. Grammar and Spelling Checker:

    • Integrate a powerful grammar and spelling checking engine to analyze the input text.
    • Highlight and categorize errors such as punctuation mistakes, tense inconsistencies, and misspellings.
    • Provide context-specific suggestions for corrections directly within the dashboard.

  6. Text Formatting Tools:

    • Offer a range of text formatting options, including:
      • Remove extra whitespace
      • Capitalization consistency
      • Remove repetitive phrases
      • Simplify complex sentences
    • Apply these transformations with user preference settings.

  7. Multilingual Support:

    • Implement automatic language detection for the input text using a reliable library.
    • Ensure all analysis tools function correctly across multiple languages, including non-English scripts.
    • Display language-specific insights and suggestions as appropriate.

  8. Export and Reporting:

    • Provide users with export options for their analysis reports, including:
      • PDF format with professional styling
      • CSV format for easy integration with other tools
      • Plain text format for sharing
    • Allow customization of the export format, such as selecting specific analysis sections to include.

  9. Performance and Optimization:

    • Optimize the performance of the application to handle large text inputs (up to 500,000 characters) without significant delays.
    • Implement caching mechanisms for repeated analysis of the same text to reduce processing time.

The final application should be polished, easy to navigate, and provide clear, actionable insights to help users improve their written content.

Original prompt (before our improvements)

Build a comprehensive text analysis tool using HTML5, CSS3, and JavaScript. Create a clean interface with text input area and results dashboard. Implement word count, character count, and reading time estimation. Add readability scoring using multiple algorithms (Flesch-Kincaid, SMOG, Coleman-Liau). Include keyword density analysis with visualization. Implement sentiment analysis with emotional tone detection. Add grammar and spelling checking with suggestions. Include text comparison functionality for similarity detection. Support multiple languages with automatic detection. Add export functionality for analysis reports. Implement text formatting and cleaning tools.