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

Annotations already declare readOnlyHint=true, so safety is covered; the description adds non-obvious operational context by disclosing the call is free and spends no credits, plus the support-level semantics (0/1/5). It says nothing about result size or pagination, but this is a small lookup endpoint.

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 short sentences, front-loaded with what the tool returns and followed by when to use it and the cost note. No filler or repetition of the title.

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 zero-required-parameter, read-only lookup with no output schema, the description covers what is returned, why to call it, and its cost profile. No output schema exists, so the description needn't explain return shape in more depth.

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 100%, with the enum, 2-char ISO constraint and support-level scale all documented in the schema itself. The description only alludes to 'per-store' and 'languages' at a high level, so it adds little beyond the schema – 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 concrete verb and resource ('List the countries AppmanAi covers') plus what each entry contains (languages, per-store support levels). That distinguishes it cleanly from sibling metadata tools like list_categories, list_features and list_tools.

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 explicit usage context: 'confirm coverage or resolve a country code before other calls,' which is a clear precondition for other calls. It does not name a disputed alternative or state when not to use it, but the guidance is concrete rather than implied.

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