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

With no annotations, the description carries the full burden of behavioral disclosure. It fails to explain pagination (despite offset/limit in schema), how multiple criteria combine (AND vs OR), or what the response format looks like. It also introduces a 'naics filter' not present in the schema, which is misleading and undermines transparency.

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 three sentences, with the first two being concise and front-loaded. The third sentence provides NAICS examples, but it refers to a non-existent parameter, making it not just wasteful but misleading. The overall length is appropriate, but the misinformation reduces effectiveness.

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 list tool with no output schema and no annotations, the description is incomplete. It does not mention pagination behavior, how criteria combine, or any return-value details. The NAICS discrepancy is a significant gap that could cause incorrect usage. Sibling context is only addressed by a vague phrase, not with concrete alternatives.

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 has 100% description coverage, so the baseline is 3; however, the description adds misleading information by instructing users to 'ask for an industry with the naics filter' and providing example codes, yet no such parameter exists. This actively harms parameter understanding. The description does not clarify relationships between min_age/max_age or other constraints, so it adds little value beyond the schema.

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 tool's purpose with a specific verb and resource: 'Build a list of companies matching criteria.' It also distinguishes from sibling tools by saying 'rather than looking one up,' which differentiates it from lookup-style tools. However, it mentions 'industry (NAICS)' as a criterion and later references a 'naics filter' that does not exist in the schema, causing slight confusion about what the tool actually accepts.

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 clear usage context: 'Use it for prospecting, market sizing, or finding every business of a kind in a place.' It also implicitly contrasts with lookup tools by saying 'rather than looking one up,' offering a hint about when not to use it. However, it does not explicitly name sibling tools or provide exclusionary guidance beyond this contrast.

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