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

With no annotations, the description carries the full burden. It discloses the required API key write scope, the human-response behavior, and the return format. It also indicates that polling is needed for updates. However, it does not mention error handling, idempotency, or potential side effects beyond ticket creation, leaving a slight gap.

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 well-structured with sections for usage, requirements, args, and returns. Every sentence adds value, and the purpose is front-loaded. It is appropriately sized for the complexity and avoids 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?

Despite having no annotations and no output schema, the description covers purpose, usage, authentication, all parameters, and return value. It is complete enough for an agent to correctly invoke the tool without needing additional external information. Minor omissions like error scenarios are not critical for basic invocation.

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 schema has no descriptions (0% coverage), so the description fully compensates by explaining each parameter: subject (short summary, max 200 chars), message (full description, max 20000 chars), category (optional with examples), and site (optional site slug). It adds constraints not present in the schema, making it highly informative.

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 action ('Open a support ticket') and the target ('BorealHost team'). It distinguishes this from sibling tools like get_support_ticket and reply_support_ticket by specifying it is for escalating platform-side problems. The verb+resource combination is specific and unambiguous.

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?

Explicitly states when to use it ('Use this to escalate platform-side problems you cannot fix with the available tools') and provides concrete examples. It also directs users to poll get_support_ticket for updates, effectively naming the alternative for tracking. This gives clear context for tool selection.

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