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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds meaningful non-annotation context: credit cost per record with a minimum charge and the absence of the 50-result cap. It does not disclose pagination depth or whether there are hard result limits beyond the cap removal, so it's slightly short of a 5.

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?

Three short sentences, front-loaded with the core purpose and zero wasted words. The cost caveat and sibling routing are both compact and relevant.

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?

With a 100%-documented schema and an output schema present, the description only needs to cover behavior and routing, which it does. It leaves minor gaps around result ordering and how many records a typical radius returns, but nothing an agent needs 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 description coverage is 100%, so the schema already documents all 7 parameters; baseline is 3. The description adds a useful usage note tying page_size to credit consumption ('keep page_size to what you need'), which is semantic guidance beyond the schema's plain 'max 100'.

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 a specific verb and resource ('Find nearby Starbucks stores from the full directory dataset') and immediately distinguishes itself from the sibling search tool. An agent can tell this geo-radius tool apart from datasets_starbucks_stores_search without opening either 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?

It explicitly names the alternative and the condition that selects it: 'Use datasets_starbucks_stores_search for text-based location queries.' It also implies the condition for using this tool (proximity/radius search without a 50-result cap). Nothing is left to inference.

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