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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful behavioral context: 'live guide counts' signals that shelf counts are current/dynamic, and 'machine-readable data rather than prose' tells the agent the output is structured, not narrative. 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?

A single, information-dense sentence with the core action front-loaded ('Get the bicycle.guide vocabulary') followed by a precise enumeration of contents. Every phrase adds value, with no filler or repetition.

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 zero-parameter, read-only tool with an output schema, the description is complete. It specifies what data is included and the format (machine-readable), and annotations cover the safety profile. Nothing necessary for correct invocation is missing.

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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameters, and the schema confirms an empty object. Nothing is missing in this dimension.

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 names a specific verb ('Get') and resource ('bicycle.guide vocabulary'), then enumerates the exact components returned: domains, shelves with live guide counts, series, personas, guide_types, and classification conventions. This clearly distinguishes it from siblings like list_guides and list_capabilities, which would return different resource types.

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 usage: if you need vocabulary/taxonomy data, use this tool. It clarifies that the data is machine-readable rather than prose, which hints at when it is appropriate. However, it never explicitly mentions alternatives (e.g., list_guides or list_capabilities) or states when not to use this tool, leaving routing largely to inference.

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