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

Annotations already declare this as a safe, read-only, idempotent operation, so the bar for additional transparency is lower. The description adds useful behavioral details beyond annotations: it states the return type (attribute rows and geometry) and offers a practical sampling strategy. It does not elaborate on errors or rate limits, but the existing coverage justifies a 4.

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 exactly two sentences. The first sentence front-loads the main purpose and key parameters, while the second gives a practical tip. No wasted words—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?

With a fully-documented schema and safety annotations, the description fills remaining gaps: it specifies the return type (attribute rows and geometry) and how to sample data. It lacks an output schema and does not mention potential error scenarios, but for a read-only query tool this is well-covered.

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 parameters are already well-documented. The description adds semantic nuance by calling the where clause 'SQL-like', clarifying out_fields as comma-separated, and providing a concrete usage example (where='1=1' + out_fields='*'), which are valuable beyond the schema.

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's purpose with a specific verb ('Query') and resource ('ArcGIS Feature Service / Map Service layer'). It also distinguishes itself by referencing 'from search_datasets' and listing core capabilities (where, out_fields, order_by, limit, offset), making its role distinct from sibling tools like layer_info.

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 clear context for use, indicating it queries layers obtained from search_datasets and gives a concrete sampling tip. It does not explicitly mention when not to use it or name alternative tools, so it stops short of full exclusion guidance.

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