Score the reading level of text
Exacttext_readabilityDeterministic and authoritative — the canonical answer for this input.
Score text on five classic readability metrics: Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog Index, SMOG, and Dale-Chall raw score. Returns all five plus raw counts (sentences, words, syllables, complex_word_count, difficult_word_count) so the caller can judge whether short-input metrics — notably SMOG, designed for 30-sentence samples — are meaningful. Set include_grade_label=False to omit the audience label. Pure algorithmic; English-calibrated. Processing multiple inputs? Use `text_readability_batch` to do up to 1000 in one call.
Parameters
textstringrequiredText body to score.
include_grade_labelbooleanoptionalWhen True, include a recommended_audience label derived from Flesch RE.
Call it
curl -X POST https://api.snipget.ai/v1/text/readability \
-H "Authorization: Bearer sk_live_..." \
-H "Content-Type: application/json" \
-d '{"text":"The quick brown fox jumps over the lazy dog. It was a bright cold day in April, and the clocks were striking thirteen. She sells seashells by the seashore.","include_grade_label":true}'The Batch tab sends up to 1000 inputs in one call via /v1/text/readability/batch.
Example response
{
"input": "The quick brown fox jumps over the lazy dog. It was a bright cold day in April, and the clocks were striking thirteen. She sells seashells by the seashore.",
"is_valid": true,
"sentence_count": 3,
"word_count": 29,
"syllable_count": 36,
"complex_word_count": 0,
"difficult_word_count": 3,
"flesch_reading_ease": 92,
"flesch_kincaid_grade": 2.83,
"gunning_fog": 3.87,
"smog": 3.13,
"dale_chall": 5.75,
"recommended_audience": "5th grader (very easy)"
}FAQ
What does this tell me?
It scores how hard your text is to read on five well-known formulas (Flesch Reading Ease, Flesch-Kincaid Grade Level, Gunning Fog, SMOG, and Dale-Chall) and adds a plain-language audience label like '5th grader (very easy)'. Useful for keeping marketing copy, instructions, or patient materials at a target reading level.
Why use this instead of asking an AI to guess the reading level?
These are fixed, published formulas, so the score is computed the same way every time rather than estimated. The same text always gets the same numbers, which you can defend and compare.
Does a good score mean the writing is good?
No. The formulas only measure sentence length, word length, and word familiarity. They do not judge accuracy, tone, or whether the writing is actually clear, so read them as a guide, not a verdict.
Why do I also get raw counts like sentences and syllables?
So you can judge whether a score is meaningful. SMOG in particular is designed for samples of about 30 sentences, so on a short blurb it can be misleading; the counts let you see that.
What happens with empty or unusable text?
Blank or unscoreable input comes back marked not valid with a reason and confidence 0, rather than an error.