Get detailed metadata for a specific web font including variants, subsets, tags, designer, year, and Google Fonts URL.
| Name | Required | Description | Default |
|---|---|---|---|
| font_id | Yes | Font slug or family name (e.g. "inter", "Open Sans", "playfair-display") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Get' clearly indicates a read-only operation, which is a positive behavioral signal. The description does not mention pagination, errors, or response format, but it does enumerate the metadata fields returned, which is helpful. It falls short of richer context like auth requirements or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately states the action and purpose. It lists specific metadata items without unnecessary filler, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description enumerates the expected fields (variants, subsets, tags, designer, year, URL), which covers return value expectations. For a single-parameter tool, this is sufficient context to understand its purpose and output, though it could mention error handling or example response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameter, including a clear description and example. The tool description does not add additional parameter semantics beyond saying 'specific web font', so it meets the baseline without exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get detailed metadata' and clearly names the resource ('a specific web font') and contents ('variants, subsets, tags, designer, year, and Google Fonts URL'). This distinguishes it from siblings like list_fonts_by_category, which lists fonts by category, and font_stack, which deals with font stacks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a specific web font' implies the tool is used when you already know the font and want its details. However, it does not explicitly mention alternatives or when not to use it, such as 'use list_fonts_by_category to discover fonts'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.