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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds behavioral detail beyond annotations: it states the return type ('attribute rows (and geometry)') and describes the query parameters (SQL-like where, out_fields, order_by, limit, offset). This adds meaningful context without contradiction.

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 three short sentences, with the core purpose front-loaded. Each sentence contributes: first defines what the tool does, second lists the key parameters, third provides a usage hint. No filler or redundant words.

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 covers the tool's purpose, all six parameters (url, where, out_fields, order_by, limit, offset), the return type, and even a sampling strategy. Since there is no output schema, it doesn't need to detail return structure further. It omits edge cases like error behavior or pagination limits, but for a query tool with this complexity, the description is sufficiently complete.

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 baseline is 3. The description adds semantic value by explaining that the query is SQL-like, by demonstrating the sample pattern (where="1=1" + out_fields="*"), and by tying the url parameter to the output of search_datasets. This goes beyond replicating schema 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 states a specific verb ('Query') and a clear resource ('an ArcGIS Feature Service / Map Service layer by its url'), distinguishing it from siblings like search_datasets (which finds datasets) and layer_info (which describes a layer). It further clarifies the tool's scope by listing the SQL-like parameters and specifying that it returns attribute rows and geometry.

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 explicitly ties the URL to search_datasets ('by its url (from search_datasets)'), indicating the preferred upstream workflow. It also provides a practical sampling tip ('Use where="1=1" + out_fields="*" to sample'). While it doesn't name alternative tools to avoid, the context makes the intended use clear.

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