Text Analysis Tool

The tool analyzes input text to quantify readability, structure, and style. It computes key metrics such as word count, sentence count, average sentence length, lexical density, and syllable-based scores. It also provides readability scores like Flesch-Kincaid and a readability band to guide editing decisions. In addition, it analyzes sentiment, formality, and modality indicators to help assess tone and audience fit.
Outputs are structured in a machine-readable JSON format and suitable for reporting pipelines. Per-text totals and optional per-sentence breakdowns are available, and users can export results as JSON or CSV for integration into workflows.
This tool benefits authors, editors, researchers, and content strategists who need objective, reproducible measures to compare drafts, benchmark versions, or support localization workflows. Its unique value lies in combining traditional readability metrics with linguistic feature analysis and tone detection in a lightweight, language-aware module.
Core features include text ingestion, tokenization, metric computation, per-sentence analytics, and ready-to-export data. Use cases include editing briefs, content audits, readability testing, and research on language quality.