Anagram Detector Skill

Overview

Anagram Detector works by normalizing both texts according to specified options, comparing character frequencies, and calculating similarity metrics. Returns detailed analysis including common characters, unique characters, and percentage similarity.

Live Test Anagram Detector Skill Skill →

The tool

Once your client is connected to the VerveKit server, this appears in its tool list as AnagramDetectorSkill. 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": "AnagramDetectorSkill",
  "arguments": {
    "text1": "listen",
    "text2": "silent"
  }
}

You do not name the tool yourself; the model picks it. Asking about listen in the terms this skill covers is enough for it to reach for AnagramDetectorSkill 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
`text1`Required	string	The first text to compare
`text2`Required	string	The second text to compare
`ignorecase`Optional	boolean	Ignore case when comparing (default: true) default true
`ignorespaces`Optional	boolean	Ignore spaces when comparing (default: true) default true

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": {
    "text1": "listen",
    "text2": "silent",
    "is_anagram": true,
    "cleaned_text1": "listen",
    "cleaned_text2": "silent",
    "sorted_text1": "eilnst",
    "sorted_text2": "eilnst",
    "length_text1": 6,
    "length_text2": 6,
    "similarity_percentage": 100
  }
}

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
`text1`	string	`listen`	The first input text provided for comparison
`text2`	string	`silent`	The second input text provided for comparison
`is_anagram`	boolean	`true`	Boolean indicating whether the texts are anagrams
`cleaned_text1`	string	`listen`	First text after applying ignore case and space options
`cleaned_text2`	string	`silent`	Second text after applying ignore case and space options
`sorted_text1`Premium	string	`eilnst`	Characters of first text sorted alphabetically
`sorted_text2`Premium	string	`eilnst`	Characters of second text sorted alphabetically
`length_text1`	number	`6`	Character count of the first text
`length_text2`	number	`6`	Character count of the second text
`similarity_percentage`Premium	number	`100`	Percentage similarity score between the two texts

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

Word Games: Validate anagrams in word puzzles, Scrabble, and anagram-based games
Cryptography: Analyze anagram-based ciphers and cryptographic puzzles
Linguistics: Study anagram relationships in language research and text analysis
Educational Apps: Create interactive tools for teaching anagrams and word patterns

Other ways to use Anagram Detector Skill

Set up Anagram Detector 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 →