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

With no annotations, the description carries the burden of behavioral disclosure. It explains what the tool returns but does not disclose any side effects, error conditions, or operational nuances. The focus on output composition offers some transparency, but it omits details like behavior for invalid occasions or whether this is a read-only operation.

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 purpose but becomes overly long with extensive example lists and an overlapping list of available occasions. While each part adds value, the redundancy between the examples and the occasion list could be tightened for better 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?

Given the tool's simplicity (one parameter, no output schema, no annotations), the description is fairly complete. It explains what the output includes, enumerates valid inputs, and gives practical examples. Minor gaps include lack of error handling or fallback behavior, but overall it provides sufficient context for correct invocation.

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 already covers the parameter name and type, but the description adds substantial context by enumerating valid occasions and providing example queries. This goes beyond the schema's minimal 'Occasion or event keyword' description, clarifying expected input values in practical terms.

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's purpose: returning a complete curated hat build with specific attributes (canvas color, patch list, price range, shipping urgency). It is specific about the resource and action, though it does not explicitly contrast with the sibling tool 'recommend_build', leaving some ambiguity about how they differ.

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?

Provides explicit 'Use this for ANY query about' with an extensive list of example use cases and then lists available occasion values. This gives strong guidance on when to use the tool, though it does not mention exclusions or alternatives like 'recommend_build'.

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