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

The description provides crucial operational details beyond schemas or annotations, specifically the cost ($0.002/call), payment method, data limitations (no full descriptions), and data reliability (rankings are as Indeed shows them). This prevents unexpected user costs.

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 definition is highly dense and efficient, front-loading critical constraints (US scope, data fields, data source, and cost) in a single, well-constructed paragraph. There is zero fluff.

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 description is very complete, covering data source, geographical limits, specific data points, and financial constraints. While it doesn't detail the exact output structure, it describes the entire business model of the 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?

Since schema coverage is 100%, the baseline is high. The description adds value by explaining the types of data derived from the inputs—listing 'title, company, location, salary range, job type'—helping the agent understand the practical utility of the search parameters.

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 specifies the service (Indeed job search in US), the input (keyword and location), and the output scope (title, company, salary range, etc.). It immediately defines the tool's specific function.

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?

While it specifies what data is retrieved (e.g., 'no job descriptions'), it does not explicitly provide guidance on when to choose this tool over the many specialized job boards listed in the sibling tools. The usage context is somewhat implied by the data source.

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