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

Annotations already establish read-only and idempotent behavior, so the description adds value by disclosing the return fields: names, OE numbers, grade, category, and CAD list price. It does not mention pagination or default limits, but the safe read-only profile makes that less critical.

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 a single, front-loaded sentence with no filler. It efficiently communicates scope, search inputs, and return values.

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 5-parameter tool with no output schema, the description covers the main search modes and return fields, but it omits the grade filter and limit/default-result behavior. The schema fills those gaps, so the overall tool remains usable, though the narrative leaves some details out.

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 description coverage is 100%, and each parameter is already documented in the schema. The description mostly paraphrases query, model, and category and does not add significant parameter-specific meaning beyond what the schema provides.

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 (search) and resource (MapleV's Tesla Model 3 / Model Y collision parts catalog) and enumerates concrete search dimensions. It is clearly differentiated from siblings such as get_part and list_categories.

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 when to use the tool—searching by keyword, OE number, model, or category—but does not explicitly state when to prefer a sibling such as get_part for a known part ID. It provides clear context but no exclusions or alternative routing.

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