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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false). With no output schema, the description usefully characterizes the return shape: plain-language outcome names paired with the products that deliver them. It does not cover ordering, volume of results, or whether the catalog is static, but adds real context beyond the annotations.

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 sentences, front-loaded with what is returned and closed with the use case. The example list earns its place by concretizing an otherwise abstract catalog, and there is no filler.

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 no-input, read-only lookup with no output schema, the description supplies exactly the missing pieces: what the entries contain and when to reach for it. Nothing an agent needs to invoke it correctly is absent.

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 takes zero parameters, so the baseline of 4 applies. There is nothing for the description to disambiguate and it introduces no misleading parameter-like language.

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 names the resource precisely — outcome-to-product mappings rendered 'in plain language with the products that provide it' — and gives concrete examples (geo-fencing, retargeting, identity resolution). The verb is only implicit (it never says 'list' or 'return'), and it does not explicitly distinguish itself from sibling list_* tools like list_categories or list_channels, but an agent can still tell what it yields.

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?

'Use this to translate what a client wants into what to ask for' gives a clear, actionable usage context: a discovery/translation step before asking for specific products. No alternative tool is named and no exclusion is stated, so the routing guidance is good but not exhaustive.

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