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

With no annotations, the description carries the full burden and does so thoroughly. It discloses that closed venues are never returned, that live open/closed state includes closing time, that hours may come as prose via hoursText rather than machine-readable openState, that seasonalCaution withholds open/closed verdicts for 79 non-year-round venues, and that provenance fields must be cited. These are substantial behavioral details beyond the schema.

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?

Though long, the description is front-loaded with purpose and every subsequent sentence earns its place by explaining behavior, return fields, attribution requirements, seasonal quirks, and the alternative tool. No filler or repetition; the length is justified by the tool's nuanced semantics.

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?

Given no output schema and a relatively complex result model, the description is complete: it names the returned fields, explains provenance and verification semantics, warns about seasonal behavior, states the maximum result count, and routes closed-venue queries to the right sibling. An agent has enough context to select and invoke the tool correctly without additional information.

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 67%, so the description must add meaning beyond the input schema. It does this for query by explaining that it searches section-specific fields and gives illustrative examples like 'pick-your-own', 'sunflowers', and 'sorbet'. It also maps the category taxonomy by listing venue types. It does not deeply elaborate town or category parameters, but the schema already describes town well and category is a self-explanatory enum, so the shortfall is modest.

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: 'Search the verified guide's venues across the Hamptons + North Fork.' It immediately distinguishes the tool's scope from generic venue search by naming covered categories and emphasizing it searches the fields each section actually keeps, not just venue names. It also distinguishes itself from recently_closed, making sibling differentiation clear.

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 explicitly states when to use an alternative: closed venues are excluded, so to ask about a closed venue by name or verify a venue from memory, use recently_closed instead. It also implicitly tells the agent this is the right tool for live, verifiable venue recommendations by describing what results contain and how to attribute them.

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