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

With no annotations, the description carries the full burden and does substantial work: it discloses the return scope (public L0 profile fields plus canonical source URLs), the ranking basis (profile-completeness quality_score), and an explicit exclusion set (no grid, price or payment fields read), which signals a read-only, safe operation. It omits auth/permission requirements and whether results are paginated beyond the limit parameter.

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, front-loaded with the usage triggers, followed by return scope and then ranking/exclusions. No restatement of the name or title and no filler; every clause adds either routing or behavioral information.

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 an eight-parameter, zero-required search tool with no output schema and no annotations, the description covers the important unknowns: what comes back, how it is ordered, and what data is deliberately not exposed. The main remaining gap is behavior with no filters supplied (return-all vs error) and any result-cap semantics, though the limit parameter partially covers the latter.

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 with examples (Guangdong, 6061, cnc-machining). The description only echoes the filterable dimensions at a high level and adds no syntax, matching behavior, or interaction semantics (e.g. process vs capability_id vs category_id) beyond what the schema states. Baseline 3 applies.

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 and resource (supplier search) plus the domain scope (Chinese factories) and the concrete question shapes it answers. An agent can tell this is a discovery/listing tool rather than a detail fetch, but the description never names the sibling it is not (get_supplier, search_works), so differentiation is inferred from the triggers rather than stated.

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?

Gives three explicit trigger scenarios — part manufacturability, process capability lookup, and filtering by region/certification/material — which is well above typical guidance. It stops short of when-not-to-use or naming an alternative tool for single-supplier lookup, so the routing decision against get_supplier is left implicit.

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