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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is clearly established. The description adds that it returns attribute rows and geometry, and that the query is SQL-like, which is useful behavior context. No contradictions 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?

Two sentences, front-loaded with the core purpose, then parameter overview, then return type and a practical tip. Every word earns its place; no fluff or repetition.

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 tool is moderately complex with 6 parameters and no output schema. The description covers the essentials: what it queries, key parameters, return content (rows and geometry), and a concrete usage pattern. It lacks explicit error handling or pagination restatement (though offset is in schema), but overall it is sufficiently complete for an agent to use 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 baseline is 3. The description adds meaningful semantics: it groups parameters into an SQL-like interface, explains the sampling pattern using where and out_fields together, and clarifies the url should come from search_datasets. This goes beyond the schema's individual 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?

Description clearly states the tool queries an ArcGIS Feature Service / Map Service layer by URL. It names specific parameters and distinguishes this from sibling tools like search_datasets (which finds datasets) and layer_info (which describes metadata). The verb 'query' and resource 'layer by its url' are precise.

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 implies the intended workflow: use this after search_datasets to query a specific layer. It provides a concrete sampling tip (where="1=1" + out_fields="*"). However, it does not explicitly state when not to use this tool versus alternatives like search_within or layer_info, so it lacks explicit exclusions.

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