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

Beyond the readOnly and idempotent annotations, the description discloses that results include both edge directions and relationship types, which is meaningful behavioral context. It does not mention potential size or pagination behavior, but the output schema covers return structure.

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?

Two sentences with no filler: the first defines the operation and output, the second gives usage guidance. The main behavioral statement is front-loaded.

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 read-only one-hop traversal with complete parameter schema, an output schema, and safe annotations, the description provides all necessary selection and invocation context. Nothing important for correct use is missing.

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%, so the description does not need to document individual parameters. 'Given a unit' and 'neighbours' maps coherently to the domain/slug start point, adding minor semantic context over the schema.

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 states a specific operation: traverse the knowledge graph from a starting unit and return its outgoing and incoming neighbours with relationship types. This clearly distinguishes it from sibling get_* tools, which retrieve individual units rather than graph adjacencies.

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?

It explicitly advises using this tool after a get_* call to widen an answer with adjacent units, giving a clear context of use relative to the retrieval family. It does not spell out explicit when-not-to-use exclusions, so it falls just short of a 5.

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