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

Annotations already cover the read-only, idempotent, non-destructive nature. The description adds that results are 'curated editorial connections' rather than exhaustive raw graph traversal, and it states the dependency on a prior search_graph result. Its mention of 'node_id' rather than the actual schema's seed_node_ids is a minor weakness, so not a 5.

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?

Three sentences with no fluff. The first sentence immediately states purpose and output; the second emphasizes the editorial differentiator; the third supplies usage context and dependency. Each sentence earns its place and the key information 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?

This is a 7-parameter tool with no output schema, but the schema descriptions fully document parameters. The description covers curation, when to use it, and the prior-search_graph dependency. It does not describe the exact return shape, which would be useful with no output schema, but the tool is still usable after reading this description.

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 baseline is 3. The description adds that the tool requires a node_id from a prior search_graph result, which reinforces the seed_node_ids parameter but does not go beyond the schema. No additional semantic depth is provided for depth, limit, direction, or relationship types.

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 names a concrete resource ('connected to a specific trend'), a specific action ('Discover what's connected'), and the types of outputs (brands, technologies, locations, cross-domain links). It clearly distinguishes itself from search_graph by claiming to return editorial connections that web search cannot provide, which separates it from sibling tools.

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 gives explicit context for when to use the tool ('after search_graph', 'map the territory', 'find which brands are connected', 'understand cross-domain relationships'). It does not explicitly name alternatives or say when not to use it, but the placement after search_graph and the limitations of web search provide strong use-case guidance.

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