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language_list

Return ISO 639 languages with code, English name and native name, filterable by query. Pure CPU, instant.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "q": "<q>"
    },
    "name": "language_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
qYesFilter by name or code

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed2 schema fields changed
    • addedInput schema / properties / q
      Added value: +{
      +  "description": "Filter by name or code",
      +  "type": "string"
      +}
    • addedInput schema / required
      Added value: +[
      +  "q"
      +]
  4. Added

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. 'Pure CPU, instant' is a genuinely useful performance trait, but the description omits whether the result set is paginated or capped, whether matching is substring or prefix, and whether an empty query returns all languages. The 'filterable' framing also softens the fact that q is required in the schema.

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?

Two short sentences, front-loaded with the resource and return fields, with the performance note as a compact trailing qualifier. No filler.

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

Completeness4/5

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

For a single-parameter read-only lookup with no annotations and no output schema, listing the returned fields is the key missing piece and it is supplied. Only minor gaps remain, such as result ordering or size limits.

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 coverage is 100% and the q parameter already documents 'Filter by name or code.' The description's 'filterable by query' adds no matching semantics (case sensitivity, substring vs exact) 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?

The description gives a specific verb and resource ('Return ISO 639 languages') and even enumerates the returned fields (code, English name, native name). It does not explicitly distinguish itself from near-neighbors like country_list, currency_list, or detect_lang, so it falls short of a 5.

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

Usage Guidelines3/5

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

'Filterable by query' implies the lookup use case, but there is no explicit when-to-use guidance, no mention of when to prefer detect_lang or translate instead, and no note that the query parameter is effectively mandatory despite being framed as an optional filter.

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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