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

Annotations already convey read-only, idempotent, non-destructive behavior, lowering the bar for disclosure. The description adds context about the data source and optional NAICS filtering, but does not describe output format, pagination, or geographic parameter dependencies. No contradiction with annotations exists.

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 two sentences with no filler. The first sentence front-loads the core data content and source; the second efficiently explains the optional filter and use cases. Every clause contributes to selection and invocation understanding.

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 9-parameter tool with no output schema, the description is somewhat thin: it names the data metrics and domain but does not explain geography-level selection rules, return structure, or units. The schema covers required parameter dependencies, but the overall package relies heavily on the schema to make the tool usable. Description is adequate but not comprehensive.

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 100%, so the baseline is 3. The description adds meaningful semantics by clarifying that NAICS is an industry filter and that the returned metrics are establishments, employment, and payroll, which helps agents interpret the year and level parameters in context. It does not fully compensate for missing schema-level nuances, but it goes beyond simple duplication.

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: business establishments, employment, and annual payroll from County Business Patterns, with an optional NAICS filter. This differentiates it from sibling census tools like census_demographics or census_population, though it lacks a direct verb such as 'get' or 'query' and does not explicitly name a sibling alternative.

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 useful usage context ('Used for industry research, competitive intel, supply chain analysis') but gives no explicit when-to-use vs. alternative guidance, such as 'for demographic data use census_demographics.' The intended use is implied by the data domain rather than clearly contrasted with sibling tools.

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