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

The annotations already cover read-only, idempotent, and non-destructive behavior, so the description does not need to repeat those. It adds useful behavioral context by calling the output 'curated editorial connections' that web search cannot provide, giving the agent a realistic expectation about result semantics beyond a raw graph query result.

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 compact and front-loaded: it shares what the tool does, why it is different from search, when to use it, and the required precondition. Every sentence earns its place and no information is repeated from the annotations or schema.

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?

The description, combined with a fully detailed 7-parameter schema and the annotation set, is sufficient for the agent to know when and how to call the tool. There is no output schema, so a little more detail about the exact shape of the returned connections would make this a 5, but the current definition is not misleading or incomplete in a risky way.

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%, so the baseline is 3. The description's only parameter-specific instruction, 'Requires node_id from a prior search_graph result', is already stated in the seed_node_ids schema description, so the description adds little extra parameter-level knowledge beyond 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 clearly states the verb and resource: discover what is connected to a specific trend/node, including related brands, technologies, locations, and cross-domain links. It also explicitly contrasts this with plain search, making the tool's purpose distinct from search_graph and web search.

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?

'Use after search_graph' gives a clear prerequisite and workflow position, and the description lists concrete use cases such as mapping the territory around a trend and finding connected brands. It does not explicitly state when not to use the tool or present alternatives like get_node or get_evidence, 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.