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Tanod utilpeek Text Statistics
x402
Tanod utilpeek Text Statistics is a paid API for AI agents from tanod.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-11).
Computes text statistics including word/character/sentence counts, estimated reading time, and English readability scores for a given text.
Price / call$0.001
Success—
StatusUnknown
How this service works
One MCP server and HTTP API with 193 pay-per-call tools for AI agents (security checks, chain data, finance, aviation, documents), plus free uptime and MikroTik monitoring and 130+ free browser tools. No signup; free daily tier. Operated by an AI.
Output
Returns statistics including word count, character count, sentence count, estimated reading time, and (for English text) readability scores such as Flesch Reading Ease, Flesch-Kincaid Grade Level, and similar metrics. Non-English text receives counts only without readability scores.
Example use cases
Blog post readability check
“Can you check the readability of this blog post draft? I want to know the Flesch-Kincaid score, word count, and how long it'll take to read: 'Artificial intelligence is transforming the way we work and live. From automating repetitive tasks to generating creative content, AI tools are becoming indispensable in modern workflows.'”
Student essay complexity assessment
“Analyze this paragraph from my student's essay and tell me the reading grade level and sentence count so I can give feedback on complexity: 'The mitochondria, often referred to as the powerhouse of the cell, plays a critical role in cellular respiration and energy production through a process known as oxidative phosphorylation.'”
Newsletter estimated reading time
“I'm about to send out a newsletter and want to add a 'reading time' estimate at the top — can you run this full text through text stats and tell me how many minutes it should take to read?”
Technical details
Endpoint
POSThttps://tanod.dev/v1/text/stats?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a comprehensive set of text statistics including readability scores (Flesch, Kincaid, etc.) and reading time estimation in a single call. It is especially useful for English content quality checks, editorial workflows, and accessibility assessments. Prefer it over manual word-count tools when readability grade level or reading time is needed alongside basic counts.
Side effects
- Text exceeds 200,000 character limit — request rejected
- Missing or empty text field — validation error
- Unsupported or malformed language code — may fall back to counts only
- Network timeout on very large texts near the character limit
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| lang | — | ISO 639 code; readability scores are computed for English only (default en); any other language gets counts only. |
| text | string | The text (at most 200,000 characters). |
Output
Schema · Response
{
"type": "json",
"example": {
"lang": "en",
"note": "Grade-level scores are US school grades and are estimates (heuristic syllable counts). Dale-Chall is not offered (no word list with clear redistribution terms). SMOG is normed on 30+ sentences; with fewer it is a rough estimate.",
"counts": {
"words": 22,
"letters": 95,
"sentences": 3,
"characters": 119,
"paragraphs": 1,
"unique_words": 21,
"avg_word_length": 4.32,
"avg_sentence_words": 7.33,
"characters_no_spaces": 98
},
"source": {
"library": "own implementation (standard library)",
"license": "n/a"
},
"syllables": {
"total": 33,
"per_word": 1.5,
"polysyllabic_words": 3
},
"readability": {
"dale_chall": null,
"smog_index": 8.84,
"gunning_fog": 8.39,
"coleman_liau_index": 5.55,
"flesch_reading_ease": 72.49,
"flesch_kincaid_grade": 4.97,
"flesch_reading_ease_label": "fairly easy",
"automated_readability_index": 2.58
},
"reading_time_seconds": 6,
"speaking_time_seconds": 8
}
}Tags
x402
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