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

Annotations already declare readOnly/openWorld/non-destructive, and the description adds substantive context beyond them: page size (20), the company_count vs. listed_count distinction with the exact stop condition ceil(listed_count / 20), default and maximum index size, and the fact that it works without an API key and reveals no contacts.

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?

Dense but front-loaded: the trigger condition leads, then the slug/no-slug behaviors are laid out parallel, then edge details. Every sentence carries operational information; nothing is filler.

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?

There is no output schema, so the description compensates by naming the returned fields (company_count, listed_count) and explaining pagination math. With auth requirements, result semantics, and mode behavior all covered, an agent has everything needed to call it correctly.

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, but the description goes further: it specifies slug casing and hyphenation with concrete examples (google-analytics, shopify) and clarifies that 'page' only applies when a slug is given and 'limit' only when it is not, disambiguating the conditional use of the 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?

States a specific verb and resource ('which companies use a particular technology', 'which technologies are most used') and explicitly splits the two behaviors by presence or absence of a slug. An agent can distinguish this from siblings like search_companies or lookup_company without opening the schema.

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?

Opens with an explicit trigger ('Use this when the user asks which companies use X') and enumerates example technologies. It also tells the agent precisely which mode applies with vs. without a slug, leaving no ambiguity about when to call it.

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