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CoCo Readability Analyzer
x402
CoCo Readability Analyzer is a paid API for AI agents from cocoeatsai.com, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-19).
Computes readability scores and text statistics (Flesch, Gunning Fog, grade level, reading/speaking time) for a given English text.
Price / call$0.001
Success—
StatusUnknown
How this service works
Zach Riehn's lab: an about-me and portfolio, a news desk, The Atelier for AI experiments, Launch Lab for XRP research, and Fracture for games.
Output
A JSON object containing word count, sentence count, syllable count, number of complex words, Flesch Reading Ease score (higher = easier), Flesch-Kincaid grade level, Gunning Fog Index, estimated reading time in minutes, and estimated speaking time in minutes, plus a note that syllable counts are estimated approximations.
Example use cases
Grade-level check for student content
“I'm writing educational material for 4th graders — can you analyze this paragraph and tell me the Flesch-Kincaid grade level and Gunning Fog score so I can make sure it's appropriate: 'Plants need sunlight, water, and soil to grow. Without these things, they cannot survive.'”
Blog post readability audit
“Before I publish this blog intro, can you run readability stats on it — I need the Flesch Reading Ease score, word count, and how long it would take to read out loud: 'Artificial intelligence is reshaping how we work, communicate, and create. The implications are vast and deeply personal.'”
Speech script timing estimate
“I have a short script I'm planning to deliver at a conference — can you tell me the estimated speaking time and sentence count for it? Here it is: 'Good morning, everyone. Today we explore the frontier of machine learning and its impact on society. Together, we'll chart a path forward.'”
Technical details
Endpoint
GEThttps://cocoeatsai.com/area4/agent/tools/readability?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, multi-metric English text readability analysis including Flesch, Gunning Fog, and time estimates in a single call, especially in an x402 micropayment context. Prefer this over manual formula implementations or heavier NLP pipelines when all you need is readability scoring without entity extraction or sentiment.
Side effects
- Missing or empty text input returns an error or zero-value scores
- Non-English text yields inaccurate syllable/readability estimates since the tool is English-only
- Very short inputs (single word or punctuation only) may produce degenerate or nonsensical scores
- Network or payment failure (402) if USDC payment is not properly attached
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| outputrequired | object |
Output
Schema · Response
{
"type": "json",
"example": {
"note": "Approximate English-language scores; syllables are estimated, not a comprehension test.",
"words": 11,
"sentences": 2,
"syllables": 14,
"gunning_fog": 5.8,
"complex_words": 1,
"reading_time_min": 0.05,
"speaking_time_min": 0.07,
"flesch_reading_ease": 93.6,
"flesch_kincaid_grade": 1.6
},
"exampleNote": "Computed offline with demonstration inputs; time/random values are illustrative."
}Tags
x402
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