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

Annotations declare readOnlyHint=true and idempotentHint=true, and the description aligns with these by not suggesting modifications. It adds useful behavior beyond annotations, such as explaining that disaster event rows include stable event_id values and that parent loc_id selects descendant rows, which are non-obvious behaviors. No contradiction with annotations.

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 concise (two sentences) and front-loads the core query capabilities before mentioning drill-down specifics. It is well-structured and every sentence adds meaningful information, but it could be slightly more structured with bullet points for clarity, though not necessary.

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?

Given the tool's complexity (7 parameters, nested objects, output schema), the description covers the main usage pattern but omits details like the output schema structure, which is available separately. It provides enough context for correct invocation, though it could mention the need for the pack_id to come from get_catalog as mentioned in the schema.

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 input schema provides 100% coverage with detailed descriptions for all parameters, but the description adds semantic context beyond the schema, such as clarifying that metrics use event_count for aggregate counts and that loc_id filters work hierarchically. This goes beyond the schema's basic parameter descriptions.

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 retrieves rows from a single published data pack with specific filtering, sorting, and limit capabilities. It distinguishes itself from siblings by mentioning the need to call get_pack first and noting that geometry families have focused next-step tools, which helps differentiate from get_catalog and get_tool_help.

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 provides clear context on when to use this tool, such as requiring get_pack to be called first and indicating that geometry families should use other tools. However, it does not explicitly state when not to use this tool or directly name alternative tools for geometry cases, so it's slightly below a 5.

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