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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds that it returns attribute rows and geometry, and demonstrates a safe sampling query, which 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?

Three sentences: purpose, parameter list, and a practical tip. No redundant explanation or boilerplate; every sentence 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?

For a no-output-schema query tool with six parameters, the description covers the URL source, return shape, and a typical query pattern. It could mention pagination behavior explicitly, but the schema includes offset and limit, and annotations cover safety, so this is reasonably 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 descriptions cover 100% of parameters, setting the baseline at 3. The description summarizes parameter names and gives a usage example, but adds little meaning beyond the schema's existing per-parameter descriptions. The sampling tip is useful but not substantive semantic enrichment.

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 'Query an ArcGIS Feature Service / Map Service layer' with a specific verb and resource, and ties it to search_datasets for sourcing URLs. This distinguishes it from siblings like layer_info (metadata) and search_within (spatial search).

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 a workflow hint ('from search_datasets') and a concrete sampling pattern ('where="1=1" + out_fields="*"'), giving clear practical guidance. However, it does not explicitly contrast with alternatives such as search_within or layer_info, so it stops short of full when-to-use vs. when-not-to-use guidance.

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