predict_price

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that it uses historical price data and returns a recommendation, confidence level, and key signals. This adds value beyond annotations.

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 a concise intro, usage note, and organized Args section. It is front-loaded with purpose and contains no fluff, though could be slightly shorter.

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 6 parameters (5 required), 0% schema coverage, and an existing output schema, the description provides sufficient context for parameter meanings and usage context. It is complete enough for an agent to use the tool correctly.

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%, but the description includes an Args section with clear explanations for each parameter, such as hotel_id being the Vervotech property ID, date formats, and currency examples. This fully compensates for the lack of 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 it predicts whether to book now or wait for a better price using historical data. It specifies the verb 'predict' and the resource 'price timing', and distinguishes itself from siblings like 'compare_rates' and 'diagnose_rates'.

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 says to call when a user asks 'Should I book now or wait?' or wants to know if a price is good. It provides clear context but does not mention when not to use or contrast with alternatives.

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