search_categories

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

Although no annotations are provided, the description fully discloses behavioral traits: it is a search (read-only implied), returns a detailed structure with fields, costs ~1 point and ~3 seconds, and pairs with downstream tools. No contradictions exist.

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 well-structured with clear sections: summary, use when, don't use, returns, pair with, and cost. Every sentence adds value, and the key information is front-loaded. It is concise yet comprehensive for the tool's complexity.

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 has only 2 parameters and no output schema, the description provides a complete picture: it explains the output format in detail, lists return fields, gives usage guidance, and mentions cost. It covers all necessary context for an AI agent to use the tool 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?

The schema covers both parameters (keyword and site) with descriptions and examples. The description adds value by explaining the purpose of keyword (Chinese or English) and providing concrete examples, which goes beyond the schema's basic description. Baseline is 3, extra context raises to 4.

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 matches Amazon's category tree by keyword and returns candidate nodes. It uses specific verbs ('Match') and resources ('Amazon's category tree'), and distinguishes from siblings by listing use cases and alternatives like get_category_paths and get_category_children.

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 provides 'Use when' and 'Don't use' conditions, including specific alternative tools (e.g., get_category_paths, get_category_children). It gives clear context for when to use—when user provides a keyword instead of a category ID—and when not to, making it highly actionable for an AI agent.

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