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check_language_support

Check which languages/scripts a font supports, or verify support for specific language codes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
font_idYesFont slug or family name
languagesNoLanguage codes to check (e.g. ["ru","ko","ar"]). If omitted, returns all supported languages.

TDQS

A3.7/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It only states the tool's function without revealing the return format, potential errors, or that it is a read-only operation. The schema does mention 'If omitted, returns all supported languages' but the description itself lacks this transparency.

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 a single, front-loaded sentence with no redundancy. It conveys both use cases (general check and specific verification) efficiently.

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

Completeness3/5

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

For a simple check tool with fully documented parameters and no output schema, the description is adequate but not comprehensive. It could mention what the response looks like (e.g., list of supported languages or boolean results) and edge cases, but it remains minimally viable.

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% with clear descriptions for both parameters (font_id and languages). The tool description adds no extra meaning beyond the schema, so the baseline of 3 is appropriate.

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 clearly states the tool's function with a specific verb ('check') and resource ('which languages/scripts a font supports'), and it distinguishes itself from sibling tools by focusing specifically on language support rather than font generation, metadata, or pairings.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool: when you need to know supported languages or verify specific language codes. However, it doesn't explicitly mention alternatives or exclusion criteria, so it stops short of a perfect score.

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

A4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: listing fonts, fetching metadata, checking language support, generating CSS, creating font stacks, and suggesting pairings. There is no overlap in their core functionalities.

Naming Consistency4/5

Most tools follow a verb_noun pattern (check_language_support, generate_css, get_font_info, list_fonts_by_category, suggest_pairings), but 'font_stack' is a noun phrase and slightly deviates from the pattern. Overall, names are consistent in style and readable.

Tool Count5/5

With 6 tools, the server is well-scoped for font metadata and CSS generation. Each tool earns its place and the count is within the ideal 3-15 range.

Completeness5/5

The tool surface covers font discovery, detailed metadata, language support verification, CSS generation, and pairing recommendations. There are no obvious dead ends; the set is comprehensive for its stated purpose.