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KiHustle Damerau-Levenshtein Scorer
x402
KiHustle Damerau-Levenshtein Scorer is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-22).
Computes a Damerau-Levenshtein edit-distance similarity score between two input strings
Price / call$0.002
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object containing a computed similarity or distance result between the two input strings (text_a and text_b), along with a status field indicating success or failure of the computation.
Example use cases
Spell-check candidate ranking
“I have a misspelled word 'teh' and want to rank these candidate corrections — 'the', 'ten', 'tea' — by how similar they are to the original. Can you score each pair using Damerau-Levenshtein distance?”
Duplicate record detection
“I have two customer names from different databases: 'Jonathan Smith' and 'Jonathon Smyth'. Can you give me a Damerau-Levenshtein score between them so I can decide if they're the same person?”
Fuzzy search relevance scoring
“A user searched for 'javascrpit' — can you score how similar that is to 'javascript' using Damerau-Levenshtein so I can decide whether to auto-correct the query?”
Technical details
Endpoint
POSThttps://kihustle.tech/bot-bazaar/api/v1/damerau-levenshtein-scorer?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a transposition-aware edit-distance metric (Damerau-Levenshtein, not plain Levenshtein) for tasks like spell correction, fuzzy deduplication, or near-match ranking. Prefer it over plain Levenshtein when adjacent character transpositions (e.g. 'teh' vs 'the') should count as a single edit. It is a low-cost, low-latency per-call scorer suitable for real-time pipelines.
Side effects
- Missing text_a or text_b fields returns an error
- Empty string inputs may return a zero-distance or edge-case result
- Very long strings may increase latency or hit limits
- Malformed JSON body results in a 400-level error
- Payment failure via x402 protocol blocks the request
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text_a | string | |
| text_b | string |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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