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

No annotations are provided, so the description carries the burden and does well: it discloses the return fields (product_id, capability_id, source_hub, price, input, relevance 0-1) and explains the `note` when nothing matched. It does not mention auth, rate limits, or empty-result behavior beyond the note, keeping it short of 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?

Two tight sentences with no waste; the core search purpose is front-loaded before the return-value detail.

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?

With no output schema and full schema coverage on parameters, the description fills the remaining gap by explaining the return shape and the weak-match note, which is exactly what an agent needs to use this tool and chain into market_invoke.

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 schema already documents limit, budget, intent, and category. The description adds only that intent is 'in plain words' and clarifies what price means relative to budget, which is marginal value 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?

States a specific verb (Search) and resource (this hub's catalogue of live data and computation) plus how to express the query (in plain words). It is clearly distinct from market_invoke, which it explicitly says its results feed into.

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 clearly frames this as the discovery step whose output (product_id, capability_id, source_hub) feeds market_invoke, and notes the `note` field for weak matches. There are no explicit exclusions or comparisons against siblings beyond market_invoke, but the routing context is clear.

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