Glassdoor reviews

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

No annotations are provided, so the description carries the full burden. It only says 'Structured', hinting at output format, but discloses nothing about pagination, rate limits, authentication, error behavior, or what happens if the URL is invalid. This is minimal behavioral context.

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 one short sentence with no filler, and the key term 'Glassdoor employee reviews' appears early. It is very concise, though it sacrifices completeness for brevity. This is not under-specification to the point of being a tautology, but it is close to the edge.

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?

The tool has a simple input schema and no output schema, so the description must explain return values and behavior. It only says 'Structured Glassdoor employee reviews', lacking details like whether reviews include ratings, dates, or pagination. For a data-extraction tool, this is incomplete context.

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 already describes the `url` parameter as 'Glassdoor company URL' with 100% coverage. The description's phrase 'for a company' adds little beyond that. Since the schema fully documents the parameter, a baseline of 3 is appropriate; no extra semantic value is provided.

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 identifies the resource as 'Structured Glassdoor employee reviews for a company', distinguishing it from sibling tool `web_data_glassdoor_company` which likely returns company profiles. However, it lacks an explicit verb like 'get' or 'fetch', making it more of a noun phrase than an action statement.

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 provides no guidance on when to use this tool versus alternatives. It does not mention `web_data_glassdoor_company` or other review-related tools, nor does it state any prerequisites or exclusions. The agent is left to infer usage from the name and one-line description.

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