cox_ai_itinerary

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

With no annotations provided, the description carries full burden. It discloses the tool's workflow and mentions using a registered prompt for consistency, which adds useful context. However, it doesn't cover important behavioral aspects like error handling, rate limits, authentication needs, or what happens if temperature data is unavailable. The description doesn't contradict any annotations since none exist.

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 clear sections: workflow overview, args, and returns. Each sentence adds value, though the 'Full workflow' line could be more concise. The bullet-point format for args and returns is efficient. It's appropriately sized for a 2-parameter tool with a specific workflow.

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's moderate complexity (2 parameters, workflow involving external data fetch and AI generation), no annotations, but with an output schema (implied by 'Returns' section), the description is reasonably complete. It explains the purpose, parameters, and output format. The main gap is lack of error handling or edge case guidance, but the output schema reduces the need to fully document return values.

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 description coverage is 0%, so the description must compensate. It provides clear semantic meaning for both parameters: 'days' as 'Number of days for the trip' and 'start_date' with format examples. This adds significant value beyond the bare schema, though it doesn't explain constraints like date ranges or day limits. With 0% schema coverage and 2 parameters, this is strong but not perfect compensation.

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: 'fetch daily temperatures + generate AI itinerary' and mentions using a registered MCP prompt. It distinguishes from the sibling 'get_activity_suggestions' by focusing on full itinerary generation rather than just suggestions. However, it doesn't specify the exact resource being fetched (e.g., temperatures for what location?), making it slightly less specific than a perfect 5.

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 implies usage for trip planning with temperature data, but doesn't explicitly state when to use this tool versus alternatives like 'get_activity_suggestions'. It mentions the workflow but lacks clear guidance on prerequisites or exclusions (e.g., whether location data is needed elsewhere).

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