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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it returns attribute rows and geometry, and supports SQL-like filtering, pagination, and field selection. This goes beyond 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 long, front-loaded with the core purpose, and every phrase contributes value. The first sentence defines scope and parameters; the second gives a concrete sampling example. No wasted words.

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 tool with 6 parameters, no output schema, and good annotations, the description covers the essential context: tool purpose, source of url, query capabilities, and return type. It even ties to the search_datasets workflow. It could be more explicit about the exact output format or handling of empty results, but it's sufficiently complete for an agent to use it correctly.

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 every parameter having a description, so the baseline is 3. The description restates the parameter list and offers one combined usage hint (sampling with where='1=1' and out_fields='*'), but it doesn't add deeper semantics to individual parameters beyond what the schema already provides.

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 identifies the exact resource type, while also referencing its origin from search_datasets, distinguishing it from sibling tools like layer_info or search_datasets.

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 usage context by indicating the url comes from search_datasets, implying a workflow: first search, then query. It also gives a practical sampling tip (where='1=1', out_fields='*'). However, it doesn't explicitly mention when to prefer an alternative like layer_info or when not to use this tool, so it falls short of a perfect 5.

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