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

No annotations are present, so the description carries the full burden and meets it: it states no authentication is required, frames the call as read-only discovery, explains that products are ordered by evidence from `brief`, and discloses that unverifiable words are flagged and `observed` numbers appear only where measured. This gives an agent an accurate safety/behavioral model before invoking.

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?

The description is well structured with WHEN TO USE, RETURNS, and EXAMPLE sections, and the purpose is front-loaded in the first sentence. It is slightly verbose, with the evidence-behavior paragraph partly restating the RETURNS section, so it is not maximally concise.

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 tool with 7 parameters, nested objects, and no output schema, the description includes a return-shape outline and an example, plus auth/behavioral context. It does not explain pagination, the wholesale/refine buying modes, or filter semantics, though the schema covers most of those; overall it is adequate but not exhaustive.

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 high (86%), so the baseline is 3. The description adds extra meaning for the key `brief` parameter — explaining how it is interpreted, that products are ranked by evidence, and that `brief_interpretation` is returned for verification — plus a concrete example call. Other parameters rely on schema descriptions, which is acceptable at this coverage level.

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?

Opens with a specific verb+resource: 'Get available DOOH advertising products and packages.' It adds the distinctive mechanism — a natural-language `brief` answered from observed screen data — and positions the tool as open catalogue discovery ('read the catalogue first, get a key when you want to transact'), separating it from transaction tools and similar inventory/price siblings.

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?

A dedicated WHEN TO USE section lists three concrete scenarios: browsing inventory before campaign creation, comparing pricing across venue types/locations, and checking availability by market/time. It gives clear when-to-use context but does not explicitly name alternatives or state when not to use this tool.

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