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

The description discloses that it returns 'best-matching cards with excerpt', indicating output format and selection behavior. It also states the corpus size (521) and defines query types. However, it does not mention edge cases like empty results or sort order, but given no annotations, it carries the burden well enough.

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 concise yet dense with useful information: purpose, query strategies, brand values, result format, and pointer to alternative. It uses a single, well-structured sentence with clear separators, and every clause adds value.

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 absence of annotations and output schema, the description provides substantial context: corpus size, query types, examples, brand filter, and result behavior. It lacks details on the 'top' parameter and result ordering, but overall it is complete enough for an agent to decide whether to use this tool.

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 0%, so the description compensates. It explains the 'query' parameter with concrete examples ('BLT421', 'FSCUT2000') and the 'brand' parameter with a list of valid values. It does not describe 'top', but this is a minor omission as it is a standard result-count parameter.

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 uses a specific verb ('Search') and clearly identifies the resource ('521 knowledge cards about fiber laser machine parts'). It immediately distinguishes itself from siblings by naming the alternative 'get_part_card' for full text, making the purpose unmistakable.

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?

It explicitly gives usage context: query by model, alarm/error keyword, or topic, and mentions an optional brand filter with a specific list of brands. It also instructs to 'use get_part_card for full text', an explicit alternative, effectively saying when not to use this tool.

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