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

Annotations already cover read-only/idempotent/non-destructive, and the description adds value on top: main number is always `main`, ids are `num_…` and stable across renames, events carry the same value as `number_id`, and either form is accepted as `number_alias`. It also states the operational constraint that only `connected` numbers can send and explains `status.at` for judging stale disconnections.

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 short paragraphs, front-loaded with the core action and the entry-point rule before the finer details about ids and aliases. A little redundancy with the schema's `status` example, but nearly every sentence carries a distinct fact.

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 single-optional-filter read tool with an output schema present, this is complete: it covers purpose, entry-point usage, alias-vs-id semantics, cross-tool interoperability, and the `connected`-required constraint. Nothing an agent needs to call it or interpret its output 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 coverage is 100%, so the `status` filter is already documented, and the description's « pass `status`, for example `disconnected` » largely repeats it. However it goes beyond by tying status to a goal (find numbers needing attention) and by explaining the semantics of `status.at` in the returned data.

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?

« List every WhatsApp number this organization has, with its status » gives a specific verb (list) plus resource (org's numbers) and immediately distinguishes itself from get_number, the sibling that fetches one. The agent can tell it apart from every other sibling without opening a schema.

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?

« Start here when you do not know which aliases exist » is an explicit routing rule, and the follow-on « the other tools' number_alias expects » tells the agent how output feeds other calls. The alternative path (get_number when you already know the alias) is implied by that framing and the pointer to filtering by status is concrete.

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