Generate a complete CSS font-stack with metric-compatible and system fallbacks for robust cross-platform rendering.
| Name | Required | Description | Default |
|---|---|---|---|
| font_id | Yes | Font slug or family name (e.g. "inter", "roboto-mono") | |
| include_system_fallbacks | No | Include system fallback fonts (default true) | |
| include_metric_compatible | No | Include metric-compatible fallback fonts (default true) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds useful behavioral context (metric-compatible and system fallbacks, cross-platform rendering) but does not explicitly state side effects, error behavior, or that it is a pure read-only operation. Since the tool is a generator, the lack of side effects is implied, but transparency is only adequate, not exceptional.
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, well-structured sentence that conveys the core purpose and key output characteristics without wasted words. It is front-loaded and efficient, earning a top score for conciseness.
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?
For a simple generator with only 3 parameters and no output schema, the description covers the main behavior and return value implicitly. It explains what the generated font stack includes (metric-compatible, system fallbacks) and the goal (cross-platform rendering). It does not provide examples or error handling, but these are not critical for an agent to use the tool correctly.
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?
Schema description coverage is 100%, so the parameters are already well-documented. The description mentions metric-compatible and system fallbacks, which relate to the boolean parameters, but does not add new meaning beyond that. It meets the baseline for schema-covered parameters.
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 clearly states the tool generates a CSS font-stack with metric-compatible and system fallbacks, using a specific verb ('Generate') and resource ('CSS font-stack'). It does not explicitly distinguish from sibling tools like generate_css, but the specificity makes its purpose unambiguous.
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 description implies when to use the tool: when a robust cross-platform font stack is needed, including fallbacks. It does not explicitly exclude alternatives or name sibling tools, but the context is clear enough for an agent to select it appropriately.
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.