get_schema

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

With no annotations, the description carries the full burden. The verb 'List' suggests a read-only operation, and the phrase 'with per-label counts' adds useful detail about the returned data. However, it does not mention any potential performance implications or whether all graph elements are always included.

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?

A single concise sentence that fully describes the tool's function with no fluff or repetition. It is front-loaded with the action and resource and leaves 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 zero parameters, an output schema, and a simple read-only purpose, the description is sufficiently complete. The tool's behavior is fully captured, and the presence of an output schema means return value details are handled elsewhere.

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?

This tool has no parameters, so baseline 4 applies. The input schema is an empty object, and the description correctly does not attempt to explain nonexistent parameters.

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 uses a specific verb 'List' and clearly identifies the resource: node labels, relationship types, and property keys with per-label counts. It is unambiguous and distinguishes from sibling tools like run_cypher or search_object by focusing on schema introspection.

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 implies usage for schema discovery but does not explicitly state when to use it over alternatives like run_cypher or provide any exclusions. A user could infer it as the go-to for schema listing, but no direct guidance is given.

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