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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds that the tool returns attribute rows and geometry, which is useful behavioral context beyond the 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 convey the entire purpose without waste. The first sentence is dense and factual, the second is a helpful tip. No redundant words or repetition of schema details.

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 moderate complexity (6 params, no output schema), the description covers the essential behavior, return type, and a recommended usage pattern. It also connects to search_datasets for context. Minor gaps like error handling or pagination behavior are not critical here.

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 the baseline is 3. The description goes beyond restating schema by explaining the SQL-like nature of `where`, the comma-separated format of `out_fields`, and by providing a practical sampling pattern. This adds value for correct parameter usage.

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 queries an ArcGIS Feature/Map Service layer by URL, which is a specific verb+resource. It distinguishes from siblings by referencing search_datasets as the source and focusing on data retrieval rather than metadata or discovery.

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 usage after search_datasets and provides a concrete sampling tip (where="1=1" + out_fields="*"). It lacks explicit exclusions or named alternatives, but the context is clear enough for an agent to understand when to invoke it.

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