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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows it is a safe read operation. The description adds value by revealing that results are 'curated editorial connections' that are not raw graph data, and expresses the important behavioral constraint that node_id must come from a prior search_graph result. No contradictions found.

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 with the core action, then adds usage instructions and a prerequisite. It is efficient, although there is minor redundancy between 'that search alone wouldn't surface' and 'that web search cannot provide', so it earns just under a 5.

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 graph traversal tool with seven parameters, the description is contextually sufficient: it names the workflow (search_graph first), the situations in which to use it, and the general nature of the return value. There is no output schema, but the description does not need to list every return field; it provides enough to understand the tool's purpose and correct call sequence.

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 every parameter is already documented in detail: graphId examples, depth defaults, limit, direction enum, seed_node_ids requirement, and relationship_types enum. The description only echoes the node_id prerequisite already present in the schema. It adds no unique parameter-level meaning, so the baseline 3 is appropriate.

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 starts with a specific verb and resource: 'Discover what's connected to a specific trend' — related brands, technologies, locations, and cross-domain links. It also explicitly distinguishes itself from plain search by saying 'search alone wouldn't surface' and returns 'curated editorial connections that web search cannot provide', making it clearly different from siblings like search_graph or get_node.

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 gives explicit usage context: 'Use after search_graph' and describes the use cases: map the territory around a trend, find connected brands, or understand cross-domain relationships. It also states the prerequisite: 'Requires node_id from a prior search_graph result.' It does not explicitly list when-not-to-use or name an alternative delta, but the use-after-search_graph guideline is clear.

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