textAnalyzer

Business

Run a full multi-dimensional analysis on Persian text — character/word counts, language ratios, readability, sentiment, keyword extraction, formality, and quality scoring. Use when building Persian writing assistants, content moderation, SEO scoring, or post-editor analytics. Triggers on mentions of analyzeText, textAnalyzer, Persian text analysis, تحلیل متن, readability Farsi, sentiment Persian, getTextSummary.

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Source SKILL.md: https://github.com/persian-tools/persian-tools/blob/HEAD/skills/textAnalyzer/SKILL.md

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textAnalyzer — Persian text analysis

import {
  analyzeText,
  getTextSummary,
  getTextComplexity,
  getTextSentiment,
  getTextKeywords,
  cleanText,
  normalizeText,
} from "@persian-tools/persian-tools";
// CommonJS
const {
  analyzeText,
  getTextSummary,
  getTextComplexity,
  getTextSentiment,
  getTextKeywords,
  cleanText,
  normalizeText,
} = require("@persian-tools/persian-tools");

Public exports

// Main API
analyzeText(text: string, options?: TextAnalyzerOptions): TextAnalysisResult

// Convenience helpers
getTextSummary(text: string): string
getTextComplexity(text: string): "ساده" | "متوسط" | "پیچیده"
getTextSentiment(text: string): "مثبت" | "منفی" | "خنثی"
getTextKeywords(text: string, limit?: number): string[]
cleanText(text: string): string
normalizeText(text: string): string

// Types
interface TextStatistics { ... }
interface TextRatios { ... }
interface ReadabilityMetrics { ... }
interface LanguageDetection { ... }
interface SentimentAnalysis { ... }
interface KeywordAnalysis { ... }
interface StyleAnalysis { ... }
interface TextAnalysisResult { ... }
interface TextAnalyzerOptions { ... }

The main function is analyzeText, not textAnalyzer. Older docs use the latter — it does not exist.

TextAnalysisResult shape

{
  originalText: string;
  cleanedText: string;
  statistics: TextStatistics;     // counts: characters, words, sentences, persian/arabic/english chars, ...
  ratios: TextRatios;             // persianRatio, arabicRatio, englishRatio, numberRatio, ...
  readability: ReadabilityMetrics;// complexity, readingTime, avgWordsPerSentence, ...
  language: LanguageDetection;    // primaryLanguage, confidence, isPurePersian
  sentiment: SentimentAnalysis;   // overall sentiment + indicators
  keywords: KeywordAnalysis;      // top keywords + frequency
  style: StyleAnalysis;           // formality / register
  suggestions: string[];          // editorial hints
  quality: ...;
}

The result is not a flat { characters, words, lines } triple — older docs claim it is. Access fields via the nested objects above.

Basic usage

import { analyzeText } from "@persian-tools/persian-tools";

const a = analyzeText("این یک متن فارسی است.");

a.statistics.totalWords;             // 5
a.statistics.totalCharacters;        // 20
a.statistics.persianCharacters;      // 15
a.language.primaryLanguage;          // "persian"
a.language.confidence;               // 95
a.language.isPurePersian;            // true
a.readability.complexity;            // "ساده"
a.readability.readingTime;           // 1 (minutes)
a.readability.averageWordsPerSentence; // 5

Convenience helpers

For one-shot lookups without the full result:

import {
  getTextSummary,
  getTextComplexity,
  getTextSentiment,
  getTextKeywords,
} from "@persian-tools/persian-tools";

getTextSummary("سلام دنیا");
// "متن شامل 2 کلمه در 1 جمله است. زبان اصلی: فارسی (100% اطمینان). زمان مطالعه تقریبی: 1 دقیقه."

getTextComplexity("این جمله ساده است");   // "ساده"
getTextSentiment("امروز روز خوبی بود");    // "مثبت"
getTextKeywords(longArticle, 5);            // top-5 keywords

Each helper calls analyzeText internally and extracts one slice. If you need multiple metrics, call analyzeText once and read the fields — don't call multiple helpers on the same text (wasteful re-analysis).

cleanText / normalizeText

cleanText(text) — applies the analyzer's display clean pass (digit conversion, diacritic strip, spacing fixes). Returns a string.
normalizeText(text) — applies the match-key normalization (used internally before counting). Use it if you want to compare two pieces of Persian text for semantic equality.

cleanText("سَلامٌ   123   دنیا");   // "سلام ۱۲۳ دنیا"

Performance

This is the heaviest utility in the library — it runs ~10 sub-analyses on the input. For real-time per-keystroke analysis, debounce. For batch jobs, prefer the convenience helpers if you only need one signal.

Common pitfalls

Function name is analyzeText, not textAnalyzer. Old docs are wrong.
Return shape is deeply nested. Don't expect flat { characters, words, lines }.
isPurePersian requires no Arabic-specific letters and no other-language tokens. Mixed-language posts will return false.
Sentiment is rule-based (indicator-word lookup), not ML. Acceptable for triage, not for nuanced sentiment grading.

References

Tests: test/textAnalyzer.spec.ts
Related: isPersian, toPersianChars, slugify skills