Suggest Font Pairing

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

Annotations already establish the read-only, idempotent, non-destructive profile. The description adds valuable behavioral context beyond annotations: deterministic curated recommendations rather than generic advice, and what the full result contains including CSS stacks, weights, source, reasoning, pairing rules, and type scale. No contradiction with annotations.

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 front-loaded with the core action, then details return value components, then adds the deterministic behavior note and a sibling integration tip. Every sentence earns its place with no filler or redundant restating of the title.

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?

With no output schema, the description sufficiently enumerates what will be returned so an agent knows what to expect. It covers the input signal, output artifacts, behavioral guarantees, and the natural follow-on tool, making the definition self-sufficient.

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 coverage is 100%, with both intent and limit already documented, so the schema carries most of the parameter meaning. The description reinforces the intent-as-vibe concept with examples but adds little new parameter-level detail.

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?

Opens with a specific verb and resource: 'Recommend production-ready font pairings' from an intent/vibe, with concrete examples. The detailed output composition (heading + body + mono CSS stacks) makes it clearly distinct from related siblings like generate_type_scale or generate_design_tokens.

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?

Gives clear context for when to call it: when the user describes a brand/product vibe and wants production font pairings. It also names a complementary next step (generate_design_tokens), though it does not explicitly state when not to use the tool or which alternatives to prefer.

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