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

No annotations exist, so the description carries full burden. It discloses that data is from US County Business Patterns and includes counts and payroll, but omits behavioral details such as data source freshness, aggregation level (state vs county), pagination, or any constraints. The scope is partially revealed.

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 only two sentences plus an example, with no extraneous content. The first sentence immediately defines the tool's purpose, and the second provides illustrative queries. Every part serves a purpose.

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 three simple parameters and no output schema, the description covers the tool's core function and typical use cases. However, it does not specify the exact return format (e.g., a table or JSON structure) or whether results are aggregated by state/industry. A bit more detail would fully inform the agent.

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 description coverage is 100%, so parameters are well-documented in the schema. The description adds example usage (e.g., California for state) but does not introduce new semantic information beyond what the schema provides (e.g., default values, NAICS code list).

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 data returned (businesses, employees, payroll by NAICS and state) and gives concrete examples like "How many tech companies in California?" It distinguishes this tool from siblings like get_demographics or get_jobs by specifying its unique focus on business patterns.

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 implies the tool is for business pattern queries but does not explicitly advise when to use it over siblings (e.g., get_jobs for employment only) or when not to use it. Example questions provide context but no direct comparison or exclusion criteria.

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