Search Flights

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is known to be a safe read operation. The description adds valuable behavioral context beyond annotations: it reveals that results are 'curated' (i.e., not exhaustive), explains the meaning of the category tags, and defines the significance of 'seats_remaining' (4 or fewer = limited availability). This helps the agent interpret results correctly and set user expectations, going beyond what annotations provide.

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: it leads with the main purpose, then breaks out the category definitions in a bulleted list, and finally explains the output fields and the seats_remaining nuance. It is a bit lengthy (around 100 words) but every sentence contributes meaning. The front-loading is effective, and the formatting aids readability. It earns a 4 rather than a 5 because some phrasing (e.g., 'the engine's recommended balance' and the seats_remaining explanation) could be tightened without losing clarity.

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 9 parameters and no output schema, the description carries the responsibility of explaining the return structure. It does this thoroughly: it lists the fields (price, total durations, layovers, categories, booking link, seats_remaining) and defines each category. It also explains the optional nature of seats_remaining. The only minor gap is that it does not explicitly mention that the output is for the specified departure date and optionally includes a return date for round trips, but the schema already documents that via the return_date parameter. Overall, it is complete enough for an agent to call and interpret results.

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 input schema has 100% coverage: every parameter includes a description (e.g., origin/destination are 3-letter IATA codes, dates are YYYY-MM-DD). The tool description adds no additional parameter-specific information; it focuses entirely on the output. Since the schema already fully documents parameters, the baseline of 3 is appropriate; the description does not need to repeat parameter details, and it does not.

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 states a clear verb ('Search') and resource ('available flights between two cities'), and then elaborates on the output categories (best, cheapest, fastest) which distinguishes the tool's value proposition. It precisely defines what the tool returns and how categories overlap. With no sibling tools, differentiation is not required, but the description is unambiguous and specific.

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 clearly implies when to use this tool: whenever flight options are needed between two cities. It does not mention alternatives (none exist), but it explains the output's curation and categories, which helps an agent decide if this tool fits the user's intent (e.g., if the user wants the fastest option). No explicit exclusions or 'when not to use' are given, but the purpose is self-evident and the description adds context about the result semantics.

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