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

With no annotations, the description carries full burden. It discloses that the tool returns 'top picks with scores and notes, seats to avoid, aircraft info, and a confidence rating.' No side effects are mentioned, but it's a read operation and the description is sufficiently informative for a recommendation tool.

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?

Four sentences, front-loaded with the main purpose, followed by inputs, outputs, and usage examples. Every sentence adds value with no redundancy. Excellent structure for an AI agent to parse quickly.

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 tool with 4 parameters (1 required, many enums, no output schema), the description covers inputs, outputs, and example queries. It lacks mention of error handling or data sources, but these are reasonable omissions for a straightforward recommendation tool.

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 baseline is 3. The description adds example values (e.g., 'UA1234') and contextual grouping of optional parameters but does not provide significant new meaning beyond the schema descriptions.

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's purpose: 'Get the best seat recommendations for a specific flight.' It lists inputs and outputs. However, it does not explicitly differentiate from sibling tools like rowhint_get_best_seats, missing an opportunity to clarify unique value.

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?

Provides positive usage examples ('Use when someone says...') and calls itself the 'easiest way,' implying it's for simple flight-number queries. But it lacks explicit guidance on when not to use it or comparisons with siblings, leaving the agent to infer boundaries.

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