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language_lookup

Resolve an ISO 639-1 language code such as en, fr, or ja to its English name and native name when you need language metadata from a two-letter code.

Use when:

  • What language does ISO 639-1 code ja refer to?

  • Get the native name for language code fr

  • Resolve a two-letter language code to its English and native names

Do not use when:

  • Translate text between languages

  • Detect the language of arbitrary free-form text

  • Look up country languages from a country code (use country_lookup)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It clearly states the tool resolves codes to English and native names, and explicitly lists non-goals (translation, detection). It does not mention behavior for invalid codes or case sensitivity, but for a simple read-only lookup, the description provides sufficient transparency about what the tool does and does not do.

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

Conciseness5/5

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

The description is highly concise and well-structured: an opening sentence states the core purpose, followed by bulleted 'Use when' and 'Do not use when' sections. Every sentence adds value, and the structure makes it easy to scan quickly.

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 simple lookup tool with one parameter and no output schema, the description is complete. It explains the input parameter, the output (English name and native name), provides usage examples, and clarifies exclusions. No additional documentation is needed for an agent to correctly invoke it.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It does so by explaining the parameter 'code' is an ISO 639-1 two-letter code with examples (en, fr, ja), which adds meaning beyond the raw schema constraints (minLength 2, maxLength 3). However, it does not discuss case sensitivity or the possibility of three-letter codes, which would be useful given the schema allows up to 3 characters.

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

Purpose5/5

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

The description uses a specific verb 'Resolve' with a clear resource 'ISO 639-1 language code' and specifies the output: English name and native name. It distinguishes itself from siblings by explicitly stating what it does not do (translate, detect) and pointing to country_lookup for country-language lookups, which is strong differentiation.

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

Usage Guidelines5/5

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

The description includes explicit 'Use when' and 'Do not use when' sections with concrete examples (e.g., 'What language does ISO 639-1 code ja refer to?') and identifies an alternative tool (country_lookup) for country-language queries, providing clear guidance on when to select this tool over others.

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

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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct data format and operation, with explicit 'Do not use when' cross-references to prevent confusion. For example, base64_encode/decode, url_encode/decode, and timestamp_convert/timezone_convert are clearly separated, and the various validators (ISBN, Luhn, UUID, JSON) apply to different identifiers.

Naming Consistency4/5

Most tool names follow an object_operation pattern (e.g., base64_decode, country_lookup, timestamp_convert), using lowercase with underscores. The main deviation is countries_bulk, which uses a noun+adjective form without an explicit operation, making it inconsistent with the verb-like operations used elsewhere.

Tool Count3/5

With 18 tools, the server falls into the 16-25 range which feels heavy for a utility collection. While each tool is individually useful and the scope is broad, the count is higher than typical for a well-focused server and may overwhelm agents scanning the available options.

Completeness4/5

The set provides solid coverage of encoding/decoding, validation, lookups, and conversions, with paired encode/decode and convert functions. However, some common utilities such as hashing, HTML entity encoding, UUID generation, or email validation are absent, leaving minor gaps for agents that need those operations.

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