booking_strategy

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

The description thoroughly discloses behavioral traits: it reads demand pressure from seasonality and equipment calendars, returns indicative recommendations (not guarantees), and mentions payment method (USDC or prepaid key). Without annotations, this fully informs the agent of the tool's read-only, analytical nature and its limitations.

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 comprehensive and well-structured, starting with the core purpose and then detailing the inputs, outputs, and behavioral caveats. While not extremely concise, the length is justified by the tool's complexity.

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?

The description provides a complete picture: inputs, internal logic, output structure (booking window, rollover probabilities, trade-off), and behavioral caveats. Without an output schema, this fully equips the agent to understand what the tool returns and how to use the 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?

Although the input schema already describes all parameters (100% coverage), the description adds value by explaining how parameters like criticality and annual_containers influence the recommendation (e.g., criticality buffer, named-account trigger). This goes beyond the schema's basic 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: to advise on booking strategy for space reservation, including recommendations for spot vs guaranteed vs named-account. It distinguishes from sibling tools like get_spot_rate (which likely just provides rates) and carrier_recommendation by focusing on the strategic booking decision with criticality and volume inputs.

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 clear context on when to use the tool (for space reservation decisions given lane, ship date, criticality) and what inputs are needed. However, it does not explicitly state when not to use or compare to sibling tools like get_spot_rate or carrier_recommendation.

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