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Text Similarity Scorer
x402
Text Similarity Scorer is a paid API for AI agents from api.kakerapetit.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).
Computes Jaccard, Dice, cosine, and overlap similarity scores between two input strings for deduplication, name matching, and near-duplicate detection.
Price / call$0.002
Success—
StatusUnknown
How this service works
Compute similarity between two texts. Returns Jaccard, Dice, cosine and overlap scores for two strings. Use to deduplicate documents, match names or titles, and detect near-identical text.
Output
Returns four numeric similarity scores between 0 and 1 for the two input strings: Jaccard (intersection over union of token sets), Dice (harmonic overlap of token sets), cosine (vector angle similarity), and overlap (intersection over the smaller set). Higher values indicate greater similarity.
Example use cases
Deduplicating customer records by name
“I have two customer names that might be the same person: 'Jonathan P. Smith' and 'Jon Smith'. Can you compare them and give me similarity scores so I know if they're duplicates?”
Detecting near-identical product descriptions
“Check how similar these two product descriptions are for me: 'Wireless noise-cancelling over-ear headphones with 30h battery' and 'Over-ear wireless headphones, noise cancellation, 30-hour battery life' — I want all four similarity scores.”
Plagiarism check between two submissions
“Can you compare these two essay excerpts and tell me how similar they are? First: 'The industrial revolution transformed society by mechanizing labor.' Second: 'Society was transformed by the industrial revolution through the mechanization of labor.' Give me the Jaccard, Dice, cosine, and overlap scores.”
Technical details
Endpoint
POSThttps://api.kakerapetit.dev/v1/text/similarityWhen to prefer
Choose this endpoint when you need multi-metric text similarity in a single call — especially when you want complementary perspectives (set-based Jaccard/Dice, vector-based cosine, and overlap) rather than a single score. Ideal for lightweight deduplication, fuzzy name matching, and near-duplicate detection on short-to-medium texts without needing a full embedding model pipeline.
Side effects
- Missing text_a or text_b field returns a 400 validation error
- Empty string inputs may produce undefined or zero scores
- Very long strings may increase latency or hit payload limits
- Non-UTF-8 or binary input may cause parsing errors
- Payment failure (402) if USDC balance is insufficient
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text_a | string | First text to compare. |
| text_b | string | Second text to compare. |
Tags
x402
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