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

Annotations declare openWorldHint=true and readOnlyHint=false, and the description appropriately explains the tool watches endpoints where the response matters but doesn't go into details like authentication requirements or rate limits. The description does add value by clarifying the semantics of what 'monitor' means here (response content matters, not just host availability), which goes beyond the annotations. However, it could have mentioned whether creation is idempotent or what happens on duplicate monitors, though the annotations cover idempotentHint=false.

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 sentences total. The first states the core purpose, the second gives concrete examples, and the third provides the pointer to the sibling tool. Every word earns its place.

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?

Given the tool has only 5 simple parameters (all covered by schema), an output schema, and useful sibling tools, the description is complete. It explains the tool's purpose, gives usage guidance, and points to an alternative without unnecessary details about return values (since output schema exists) or parameter syntax (since schema covers them).

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 parameters are well-documented in the schema. The description adds conceptual context for the 'name' parameter ('Something recognisable months later beats the bare hostname') and clarifies the tool focuses on response content. While the description itself doesn't enumerate parameters, it works with the fully-covered schema to give complete semantic understanding. The description could have added more behavioral details about how parameters like frequency interact with monitoring behavior, but the schema covers the basics well.

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 this tool watches JSON/REST endpoints where the response content matters, distinguishing it from a plain page check. It names the specific use case (health endpoints, webhooks, APIs) and explicitly contrasts with create_http_monitor, making the purpose and differentiation clear.

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 explicitly says when to use this tool ('for health endpoints, webhooks and any API whose failure would be invisible to a plain page check') and provides a concrete alternative ('For an ordinary web page, create_http_monitor is lighter and enough'). This is a model example of usage guidance.

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