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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and closed-world behavior. The description adds useful provenance/scope context ('only verified opt-in public') and a data-interpretation caveat ('no availability or demand inference'). It does not describe result shape, pagination, or matching behavior, so the added value is modest.

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?

It is a single front-loaded sentence with no filler, so it is concise and structurally efficient. The brevity is not wasted, though it leaves substantial gaps addressed under contextual completeness.

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 13-parameter search tool with no output schema, the description covers only a broad scope constraint. It gives no filter usage guidance, no return format expectations, and no indication of how results relate to the many sibling search tools. Annotations cover the safety profile, but the description is far too thin for the tool's complexity.

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?

The tool has 13 parameters with 0% schema description coverage, and the description provides no information about any of them. With no parameter semantics in the schema and none added by the description, an agent has no guidance on how filters such as moq, capacity, hs_cn_code, canonical_concept_id, or source_language should be used.

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 verb and resource ('Search ... manufacturer projections') plus a data scope ('verified opt-in public'). However, 'projections' is undefined jargon, and it does not differentiate this tool from siblings like search_suppliers, search_products, or search_opportunities. The purpose is inferable but not crisp.

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?

There is no explicit when-to-use guidance, no alternatives named, and no prerequisites. The phrase 'no availability or demand inference' is a caveat about interpretation, not a routing rule for choosing this tool over a sibling.

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