suggest_pairing

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

With no annotations, the description carries the full behavioral burden. It discloses the return format ('ready-to-use @import URLs and CSS stacks') and the underlying design principle ('the contrast reads as deliberate'), which is meaningful context. It does not mention whether multiple pairings are returned or address edge cases, but the core behavior is transparent.

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 single sentence packs the action, the design rationale, and the output format in one economical sentence without repeating schema fields. Every clause earns its place, and the key verb-resource pair is front-loaded.

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 one-parameter tool with no output schema, the description covers the purpose and the return value, and the schema covers the parameter. What is missing is an explicit statement of result count or the default behavior, but that is a minor gap. The description is adequately complete for an agent to invoke it 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 coverage is 100%: the single 'mood' parameter already has an enum and description. The tool description only repeats the notion of 'a mood' without adding syntax, defaults, or interpretation details. Baseline 3 is appropriate because the schema does the heavy lifting and the description adds only a slight purpose linkage.

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 opens with a specific verb and resource: 'Suggest display-and-body font pairings for a mood.' It further specifies the design intent ('pairing across a category boundary so the contrast reads as deliberate') and the concrete deliverable ('Returns ready-to-use @import URLs and CSS stacks'). This clearly distinguishes it from the sibling suggest_fonts, which presumably suggests individual fonts rather than pairings.

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 gives a clear condition for use ('for a mood') but never states when to prefer this tool over suggest_fonts or when not to use it. The agent has to infer that pairings are the target output from the name and description; there is no explicit alternative routing or exclusion. This is implied usage at best.

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