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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds genuine beyond-annotation context: the backends handshake is described as 'cheap', reachability values are enumerated ('ok'/'unreachable'), and the effect of check_backends on scope (every configured country backend) is disclosed.

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 core sentences are front-loaded and dense, but the leading German sample utterance is unlabeled, untranslated and detached from the rest of the English text, so its contribution is unclear. Odd indentation and a stray blank line add noise without information.

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 one-parameter probe this covers everything an agent needs: what it proves, the opt-in deep check, the returned shape, and which sibling to use instead. An output schema exists, so the extra return-value detail is a bonus rather than a gap-filler.

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 description coverage is 0%, so the description must carry the load, and it does: check_backends is described with its default (false) and the precise behavioral difference when true. That is more than the bare boolean type in the schema provides.

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 a specific operation (liveness probe confirming the unified register server is up) and explicitly scopes it as a service-availability check rather than a data query. It also differentiates itself from get_coverage, so an agent can separate it from the data-oriented siblings without reading the 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?

It states the alternative explicitly: 'Use get_coverage for data completeness; this tool only says whether the service is up.' It also gives the condition for enabling check_backends, so both invocation decisions are covered.

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