Levenshtein Distance Skill

Overview

Ideal for spell checking, fuzzy matching, plagiarism detection, and any application requiring string similarity measurement.

Live Test Levenshtein Distance Skill Skill →

The tool

Once your client is connected to the VerveKit server, this appears in its tool list as LevenshteinDistanceSkill. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

Tool call

{
  "name": "LevenshteinDistanceSkill",
  "arguments": {
    "string1": "kitten",
    "string2": "sitting"
  }
}

You do not name the tool yourself; the model picks it. Asking about kitten in the terms this skill covers is enough for it to reach for LevenshteinDistanceSkill on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every skill in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervekit": {
      "url": "https://api.vervekit.com/v1/mcp"
    }
  }
}

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

Argument	Type	Description
`string1`Required	string	First string to compare (max 10,000 characters)
`string2`Required	string	Second string to compare (max 10,000 characters)

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

Result

{
  "status": "ok",
  "error": null,
  "data": {
    "distance": 3,
    "similarity": 57.14,
    "matchLevel": "medium",
    "string1Length": 6,
    "string2Length": 7,
    "string1": "kitten",
    "string2": "sitting"
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Field	Type	Example	Description
`distance`	number	`3`	The Levenshtein edit distance between the two strings
`similarity`	number	`57.14`	Similarity percentage from 0 to 100
`matchLevel`	string	`medium`	Similarity level: exact, high, medium, low, or none
`string1Length`Premium	number	`6`	Length of the first string
`string2Length`Premium	number	`7`	Length of the second string
`string1`Premium	string	`kitten`	The first input string
`string2`Premium	string	`sitting`	The second input string

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

Status	What it means
`400` / `422`	The arguments did not validate. The message names the offending one.
`401`	The OAuth session is invalid or expired — reconnect the server.
`403`	Blocked by a key restriction or an IP allow-list. Never a bad identity.
`404`	This skill is not part of VerveKit. Check the catalog.
`429`	Out of credits, or a brief rate limit. The message tells them apart.

A call costs 2 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

Spell Checking: Calculate similarity between misspelled words and dictionary entries
Fuzzy Search: Implement approximate string matching for search engines
Plagiarism Detection: Measure text similarity for detecting copied content
Data Deduplication: Identify near-duplicate records in databases

Other ways to use Levenshtein Distance Skill

Set up Levenshtein Distance Skill on VerveKit, or reach the same source a different way. Your VerveKit account and credits work on all of them — one key, one balance.

Call it as a REST APIOne HTTPS endpoint and an x-api-key header, with SDKs for Node, Python and .NET.APIVerve →Reference →

Google Sheets or ExcelA =VERVE() formula fills a column — no script, no export, recalculates in place.VerveSheets →Reference →