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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only states what is returned, with no mention of side effects, authentication needs, or any behavioral traits beyond being a read operation. This is insufficient for a tool with no 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?

The description is a single sentence that front-loads the verb and result, with no wasted words. It is concise and directly conveys the tool's action.

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 simple tool with no parameters or output schema, the description covers the essential return value. However, it lacks any context about when to use it or behavioral constraints, which slightly detracts from completeness. Still, it is mostly adequate given the tool's simplicity.

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 input schema has zero parameters and 100% coverage, so the description adds value by explaining the output (what is returned). Since there are no parameters, the baseline is high, and the description effectively clarifies the tool's purpose.

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 clearly states the tool returns the verified public WhatsApp contact and canonical website, specifying the verb 'returns' and the exact resources. It distinguishes from sibling tools (get_operational_boundaries, get_service_overview) which focus on different information.

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 does not provide explicit guidance on when to use this tool versus alternatives. There are no usage conditions or exclusions, but the context implies it is for retrieving public contact info. This is adequate but lacks clarity for an LLM to decide between siblings.

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