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

With no annotations provided, the description carries the full behavioral burden. It discloses that this is a forecasting tool rather than a live availability search, and specifies what the output covers (average/min/max rates by star rating over a date window). This gives the agent an accurate mental model of the tool's behavior without misrepresenting its nature.

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 compact, front-loads the core purpose, and includes only useful context: the forecasting nature, the output fields, example questions, and an exclusion. The additional knownInformation block is relevant for interpreting date defaults and does not add noise.

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?

Despite lacking an output schema, the description explains the key return dimensions (average, minimum, maximum by star rating over a date window). Combined with a fully documented input schema and the known current date, the agent has enough context to invoke the tool correctly. Minor gaps such as data-source caveats or exact response shape slightly prevent a top score.

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 100%, so the schema already fully documents the parameters and their formats. The description adds a high-level summary but no parameter-specific details beyond what the schema provides. A baseline of 3 is appropriate because the schema does the heavy lifting.

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 specific verb ('Forecast') and resource ('monthly hotel price trends for a destination'), and clearly enumerates the output dimensions: average, minimum, and maximum nightly rate by star rating across a date window. It also explicitly distinguishes itself from a live-availability search, which helps separate it from sibling tools like trivago_accommodation-search.

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 explicit use cases ('when is the cheapest month to visit X', 'how do prices change through the year') and an explicit when-not-to-use ('not a live-availability search'). It does not name a specific alternative tool, but the context and exclusion are clear enough for an agent to route appropriately.

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