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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new context: the exact result fields returned (name, slug, tagline, jobs, pricing model, HQ country, icon, links, total match count) and the CC-BY-4.0 attribution obligation with infrabase_url — useful operational detail the annotations do not carry.

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 front-loaded sentences that move from scope to filters to returns to attribution; each sentence carries information. It is slightly dense and could trim the long product-category enumeration, but nothing is wasted or repeated.

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 present, the description compensates by enumerating the returned fields and the total match count. All seven parameters are schema-documented, the paging params are self-evident, and the attribution/licensing requirement is disclosed — nothing an agent needs to call this correctly is missing.

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 all seven parameters (query, category, job, gdpr, eu_only, limit, offset) are already documented in the schema. The description restates the filter dimensions at a high level but adds no syntax, format, or interaction detail beyond what the schema provides, so the 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 ('Search Infrabase.ai, a hand-verified directory of AI infrastructure products') and enumerates the domain covered (inference APIs, GPU clouds, vector databases, etc.). It clearly distinguishes itself from siblings get_tool and find_alternatives by positioning those as downstream consumers of the returned slug.

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 establishes clear context by naming the filter axes (free text, category, job, European HQ) and by noting that each result's slug feeds get_tool and find_alternatives, which implies the intended workflow. It stops short of explicitly stating when to prefer this over siblings like list_european_providers or when not to use it.

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