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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds behavioral context beyond annotations: it mentions the return format ('returns attribute rows (and geometry)'), the SQL-like query syntax, and pagination parameters ('limit', 'offset'). This is meaningful additional information about what the tool does.

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 purpose, and includes all necessary usage context without redundancy. Every phrase earns its place: the source of the URL, key parameters, return type, and a practical tip. It is concise and well-structured.

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 complexity (6 parameters) and the absence of an output schema, the description covers the essential context: what the tool does, where the URL comes from, how to use the key parameters, and what it returns. It does not delve into error handling or output formatting, but the schema and annotations fill in details. This is a high level of completeness for a query 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 description coverage is 100%, with each parameter already having a description. The description reinforces the semantics by collectively referring to them as 'SQL-like' and lists their order, but adds little beyond the schema. The sampling tip is usage guidance rather than parameter semantics. Baseline 3 is appropriate.

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: 'Query an ArcGIS Feature Service / Map Service layer by its url'. It uses a specific verb (Query) and resource (layer), and distinguishes itself from siblings by referencing search_datasets as the source of the URL. It also specifies the return type ('attribute rows (and geometry)'), which further clarifies its role.

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 gives clear context for when to use the tool: it queries a layer 'from search_datasets', implying it follows dataset discovery. It provides a practical sampling tip ('Use where="1=1" + out_fields="*" to sample') which guides usage. However, it does not explicitly mention when not to use it or alternatives like layer_info, but the context is sufficient.

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