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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds behavioral context by stating it returns attribute rows and geometry, and mentions pagination via offset and limit. This goes beyond the annotations without contradicting them.

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 two sentences, front-loaded with the core action and parameter list. Every sentence adds value, and there is no redundancy or filler.

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 six parameters and no output schema, the description covers the tool's purpose, key parameter behaviors, return type (attribute rows and geometry), and a practical sampling pattern. It could mention error handling or response structure, but it is sufficient for an agent to select and invoke the tool.

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% with descriptions for all six parameters. The description adds little semantic value beyond the schema—it reiterates 'SQL-like where' and 'comma-separated out_fields' which are already in the schema. The sampling tip is useful but more about usage than parameter meaning.

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 'Query an ArcGIS Feature Service / Map Service layer by its url', providing a specific verb and resource. It distinguishes from sibling tools like search_datasets (which finds datasets) and layer_info (which likely describes metadata) by focusing on querying layer data.

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 provides workflow context by noting the URL comes from search_datasets, and includes explicit usage tips such as using where='1=1' with out_fields='*' to sample. While this gives clear context, it does not explicitly exclude when not to use the tool or name alternative tools for different scenarios.

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