get_health

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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior. The description adds valuable context: the public endpoint redacts internal details, it is unauthenticated, and it performs a single GET with no destructive actions. This fully discloses behavior without contradicting 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 compact and front-loaded, with every sentence adding value: purpose, scope, return values, redaction behavior, usage guidance, alternative tool, and safety/auth notes. No filler or redundancy.

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-parameter health probe with rich annotations, the description is fully self-sufficient. It covers purpose, expected outputs, safe-call context, when to use it, and when not to, leaving no meaningful gaps.

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 has zero parameters, so the baseline is 4. There is nothing to explain beyond what the empty schema already communicates; no additional parameter guidance is needed.

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 is a read-only health probe for the IntoDNS.ai backend itself, immediately distinguishing it from tools that probe target domains. It specifies exact outputs (service status and observation timestamp) and differentiates from get_stats.

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?

Explicit usage guidance is provided: use as a pre-flight check before batch jobs or to distinguish service incidents from DNS findings. It also names an alternative tool (get_stats) for public usage counters, making the boundary clear.

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