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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely useful context beyond that: the rows are fake, using reserved example domains, and the response also includes a column reference. It does not say anything about pagination or row limits beyond the schema's maximum of 10.

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?

A single dense sentence that front-loads what is returned and appends the crucial caveat that the data is not real. Nothing is wasted, though the parenthetical is slightly heavy.

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 must convey the return shape, and it does: rows in the exact delivered format plus a column reference. Combined with a fully documented single parameter and rich annotations, an agent has enough to invoke and interpret this correctly; only the relationship to real-data tools is left to inference.

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% — count is fully documented with default, min and max — so the schema carries parameter meaning. The description adds nothing about the count parameter, which is fine given full coverage, and the baseline of 3 applies.

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 states the resource concretely — illustrative lead rows in the exact delivered format plus a column reference — so an agent knows it returns sample data, not a computation or a mutation. It is clear on its own but never names or contrasts itself with the sibling quote_lead_list, which is the tool that returns real leads.

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?

Usage is only implied: the parenthetical '(placeholder businesses on reserved example domains, not real leads)' hints this is for inspecting format before ordering or quoting, and implicitly points away from real-data tools. There is no explicit when-to-use, no prerequisites, and no named alternative.

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