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

Beyond the sparse openWorldHint annotation, the description discloses meaningful behavioral traits: availability restrictions, a monthly quota, a 60-second per-incident cooldown, and scoping limitations. This is strong disclosure for a diagnostic action that may consume quota and have rate constraints.

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 concise and front-loaded with the core purpose, then adds operational constraints in separate, clearly scoped sentences. Every sentence contributes useful information without redundancy or fluff.

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 only two required parameters, no output schema, and minimal annotations, the description covers the essential operational context: what the tool does, plan restrictions, quota/cooldown, and ownership scope. It does not specify exact output formatting, but 'plain-language AI diagnosis' sufficiently indicates the return nature for this tool's complexity.

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 schema already fully documents monitor_id and incident_id. The description adds no additional parameter-level meaning, such as ID formats or validation rules, so the baseline score of 3 is appropriate.

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 uses a specific verb-resource pair: 'Generate ... a diagnosis for a specific incident.' This clearly distinguishes the tool from data-retrieval siblings like get-monitor-incidents and list-all-incidents by emphasizing an AI-generated plain-language diagnosis rather than raw incident data.

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 provides useful constraints—plan availability, monthly quota, cooldown, and strict scoping to the token owner's monitors—but does not explicitly state when to prefer this tool over alternatives or when not to use it. Usage context is implied rather than directly routed against sibling tools.

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