select_by_attribute

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

No annotations provided, so description carries the burden. It states the tool 'reads in_features, applies where_clause, and writes selected rows to out_features,' which gives basic behavior but lacks details on overwrite behavior, error conditions, or permission needs. It does not contradict any 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?

The description is two sentences, front-loaded with the main purpose and immediately followed by usage guidance. Every sentence adds value with 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?

Given the presence of an output schema and the tool's moderate complexity (4 params, 1 required), the description covers the core functionality, usage context, and high-level parameter roles. It does not detail overwrite or path constraints, but those are in the schema, so completeness is good.

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 0%, so the description must compensate. It names the three main parameters (in_features, where_clause, out_features) and explains their role in the action, but does not add detailed semantics beyond what the schema's property descriptions already provide. This is adequate but not exceptional.

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 materializes a SQL attribute query into a new feature class using ArcPy Select, which is a specific verb and resource. It also distinguishes from siblings like select_by_location by specifying 'saved subset rather than an in-memory layer selection.'

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 explicitly says 'Use this when a stateless MCP workflow needs a saved subset rather than an in-memory layer selection,' providing clear when-to-use and implying alternatives. This differentiates from other selection tools.

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