describe_data

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

With no annotations provided, the description carries the full burden. It discloses that the tool produces a description (type, spatial reference, etc.) and works on many dataset types. However, it does not explicitly state that the tool is read-only, has no side effects, or mention performance implications. For a descriptive tool, this is minimally adequate but lacks depth.

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 consists of two short sentences with no wasted words. It front-loads the key output attributes and then expands on supported input types. Very efficient and scannable.

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 tool's simplicity and the existence of an output schema (which covers return structure), the description is largely complete. It explains what the tool does, what inputs it accepts, and what outputs are described. Minor gaps include error handling and behavior for unsupported types, but these are not critical for a basic descriptive 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?

The input schema has 0% description coverage, so the description must compensate. The tool description mentions that it works on various dataset types, indirectly clarifying the 'path' parameter as a dataset path. However, it does not explain valid formats, absolute vs relative paths, or provide examples. The parameter remains underdocumented.

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 'Describe a dataset' and lists specific attributes (type, spatial reference, extent, fields, row count), making the tool's purpose unambiguous. It also specifies the input types (feature classes, shapefiles, rasters, etc.), distinguishing it from the sibling tool 'describe_gp_tool' which likely describes geoprocessing tools instead.

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 no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or scenarios where other tools (e.g., 'describe_gp_tool' or 'inspect_project') would be more appropriate. The agent is left to infer usage context.

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