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

Annotations already cover readOnlyHint, idempotentHint, and openWorldHint, so the bar for additional context is met by the description's behavioral details: the dataset is frozen at 2011, the default filter excludes prospects/occurrences, and commodity matching is case-sensitive against the commodities[] array. These are exactly the kinds of non-obvious traits an agent needs to know.

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 dense sentences deliver dataset provenance, row contents, filter behavior, usage examples, and parameter semantics without redundancy. The most important information (purpose and scope) is front-loaded, and every clause earns its place.

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?

The description is largely complete for a read-only query tool: it enumerates the row fields returned, explains the default filter and include_minor behavior, and clarifies commodity matching. It omits pagination details and any discussion of the bounding-box parameters, but given the schema annotations and the simplicity of spatial bounds, this is a minor gap.

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?

With schema coverage at 56%, the description compensates notably: it explains commodity case-sensitivity, include_minor's effect on the default filter, and the presence of commodity fields (commod1/2/3) not fully detailed in the schema. The lat/lon bounds are left to inference, but they are standard spatial parameters and the required coordinate set is already in 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 opens with 'Query mineral deposits from the USGS Mineral Resources Data System', naming a specific verb and resource, and adds substantive context: public-domain government dataset, ~304k records, 2011 archival snapshot. The usage examples ('lithium mines in Chile', 'rare-earth deposits worldwide') further pin down the tool's scope, making it clearly distinct from sibling query_* tools.

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 gives explicit usage scenarios ('Use for questions like...') and explains the default significant-sites filter and how to override it with include_minor. It does not, however, name alternative tools or state when not to use it, so it stops short of full when/when-not guidance.

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