Skip to main content
Glama

Duo Data Utilities: IBAN, ISIN, VAT & Tax ID, Barcode, Timezone, Geo APIs

Slug generator: Unicode-aware URL slug with transliteration

slug_generate
Read-onlyIdempotent

Slug generator: turn arbitrary text into a URL-safe slug. Decomposes accents, transliterates German umlauts, Scandinavian and Turkish letters, the ligatures that lose meaning under plain NFD, and Cyrillic (Russian, Ukrainian, Belarusian, Bulgarian, Serbian, Macedonian; language from lang or inferred from the letters). Lowercases, collapses separators, truncates on a word boundary. Returns the slug plus what was removed. Price: $0.05 per successful call, paid over x402 (USDC on Base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxNoMaximum slug length 1-512, default 96. Truncates at the last complete word. Accepted: integer 1-512.
caseNolower (default), preserve or upper. Accepted: lower, preserve, upper.
langNoISO 639-1 code for locale-sensitive folding (de: ü->ue) and the Cyrillic table (ru, uk, be, bg, sr, mk). Default locale-neutral; for Cyrillic the language is then inferred from letters unique to Ukrainian, Belarusian, Serbian or Macedonian, else Russian BGN/PCGN letters with ISO 9 (accents folded) for the rest. Accepted: an ISO 639-1 language code.
textYesText to slugify, at most 2048 characters. Accepted: at most 2048 characters.
separatorNoSeparator: - (default), _, . or empty. Accepted: -, _, . or empty.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover read-only/idempotent/local behavior, but the description adds genuinely new context the annotations cannot: a per-call price ($0.05 over x402 with USDC on Base), the fact that it returns the slug plus what was removed (no output schema exists), and the word-boundary truncation behavior. Payment/auth requirements are exactly the kind of disclosure annotations cannot carry.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core verb+resource, then progressively narrower detail, ending with the pricing fact. Slightly dense in the middle sentence enumerating letter groups, but each sentence carries usable information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a stateless transform with no output schema, the description fills the needed gaps: what is produced (slug plus a removal report), the pricing model, and the folding behavior. Nothing essential to invoking it correctly appears to be missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents max, case, lang, separator and text in detail. The description largely restates the same transliteration rules (umlauts, Cyrillic table, language inference) rather than adding syntax or constraints beyond the schema, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete verb+resource ('turn arbitrary text into a URL-safe slug') and scopes it well: accent decomposition, umlaut/Scandinavian/Turkish ligature/Cyrillic transliteration, lowercasing, separator collapsing, word-boundary truncation. It does not explicitly distinguish itself from the sibling cyrillic_transliterate or punycode_convert, so the sibling differentiation is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use or when-not-to-use guidance and no routing to alternatives. It never says how it differs from cyrillic_transliterate (which overlaps on the Cyrillic case) or punycode_convert, so an agent must infer which tool to pick.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.