ZeroGPT AI Detector, Readability & NLP Linguistic Analyzer

An all-in-one AI detection, comprehensive readability scoring, and natural language processing (NLP) analyzer powered directly by ZeroGPT.cc.

Analyze any text for AI generation (ChatGPT 4o, Claude 3.5, Gemini, LLaMA, DeepSeek), compute 8 industry-standard readability algorithms, audit part-of-speech grammatical syntax, and detect passive voice constructions.

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🚀 5 Powerful Feature Suites in One API

1. 🤖 Deep AI Content Detection & Real vs. Fake Probabilities

• real_probability & fake_probability: Precise numerical confidence metrics measuring authentic human vs. AI-generated text.
• html_content: Interactive sentence-by-sentence HTML visualization highlighting suspected AI sentences with tooltips.

2. 📚 8 Industry-Standard Readability & Grade-Level Indices

• readability: Overall Flesch Reading Ease score.
• flesch_kincaid_grade: US school grade level required to understand the text.
• gunning_fog: Gunning Fog Index evaluating text complexity.
• coleman_liau_index: Characters-per-word readability formula.
• automated_readability_index (ARI): Automated readability metric.
• smog_index: Simple Measure of Gobbledygook (SMOG) for academic and medical texts.
• dale_chall_readability_score: Comprehension difficulty based on familiar vocabulary.
• linsear_write_formula: Technical and military readability score.
• readability_text: Sentence-by-sentence readability breakdown with interactive HTML styling.

3. 🧠 Lexical Complexity & Vocabulary Statistics

• percentage_sat: Percentage of advanced SAT-level academic words.
• percentage_common: Proportion of common, high-frequency words.
• words_three_syllables: List of polysyllabic (3+ syllables) complex words.
• syllable_count, monosyllabcount, & polysyllabcount: Detailed syllable distributions.
• reading_time: Estimated reading time in minutes.
• sentence_length: Average word count per sentence.
• all_tokens, used_tokens, lexicon_count, sentence_count, char_count, letter_count.

4. 📝 Syntactic Grammar & Part-of-Speech (POS) Breakdown

• nouns_count & proper_nouns_count
• verbs_count
• adjectives_count
• adverbs_count
• pronouns_count
• prepositions_count
• conjunctions_count
• determiners_count
• interjections_count
• qualifiers_count

5. 🔍 Passive Voice Detection & Construction Audit

• passive_sentence_count: Exact count of sentences written in passive voice.
• passive_sentences: Structured HTML highlighting passive constructions for clear editing.

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📥 Input Schema

Field	Type	Description	Default	Required
text	String	The text document, essay, article, or code documentation to analyze.	""	Yes

Example Input:

{
  "text": "Dear Hiring Manager, I am writing to express my strong interest in the senior software engineer position. Over the past seven years, I have architected high-performance distributed systems with 99.99% uptime."
}

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📤 Output Schema

{
  "all_tokens": 38,
  "used_tokens": 38,
  "real_probability": 0.9844,
  "fake_probability": 0.0155,
  "readability": 53.71,
  "percentage_sat": 12.5,
  "percentage_common": 65.0,
  "sentence_length": 15.5,
  "reading_time": 1.95,
  "flesch_kincaid_grade": 13.9,
  "coleman_liau_index": 12.8,
  "automated_readability_index": 11.2,
  "dale_chall_readability_score": 9.4,
  "gunning_fog": 13.5,
  "smog_index": 0.0,
  "linsear_write_formula": 14.0,
  "syllable_count": 52,
  "monosyllabcount": 22,
  "polysyllabcount": 8,
  "words_three_syllables": ["Manager", "interest", "engineer", "architected"],
  "sentence_count": 2,
  "char_count": 218,
  "letter_count": 212,
  "lexicon_count": 31,
  "nouns_count": 10,
  "proper_nouns_count": 3,
  "verbs_count": 7,
  "adjectives_count": 4,
  "adverbs_count": 1,
  "conjunctions_count": 1,
  "determiners_count": 3,
  "prepositions_count": 4,
  "pronouns_count": 3,
  "passive_sentence_count": 0,
  "passive_sentences": "<div style='overflow-wrap: break-word;'></div>",
  "html_content": "<div class=\"highlightResult\">...</div>",
  "readability_text": "<div class=\"highlightResult\">...</div>"
}