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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description does not need to repeat those. It adds useful context about the source ('published cases') and match semantics ('mention'), but it does not disclose response shape, pagination behavior, or whether matching is exact.

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 10-word sentence that front-loads the action and resource. No wasted words and the key scope ('published cases that mention...') is immediately clear.

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 simple read-only lookup with annotations covering safety, the description is mostly sufficient. It omits what the returned cases look like and how industry matching works, which matters more because there is no output schema.

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?

With 0% schema description coverage, the description must carry semantic weight. 'Requested industry' clarifies the purpose of the required industry parameter, but limit is not described and match behavior is left unspecified. The schema's name, default, and bounds make limit largely inferable, so this is adequate but not strong.

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 action ('Find') and resource ('published cases') filtered by industry, so its purpose is clear. It stops short of explicitly differentiating itself from siblings such as search_cases or get_case, though the industry focus is a strong implicit cue.

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?

No guidance is given on when to choose this tool over alternatives like search_cases or get_case. The agent must infer from the tool name and sibling list that this is the industry-experience-specific lookup.

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