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

The description adds significant context beyond annotations, detailing crucial behavioral traits like data fidelity rules ('keep dish names and prices exactly as written'), translation capabilities, and the side effect of non-idempotency (retrying creates a new link). This manages user expectations well.

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 dense but highly efficient. Each sentence conveys a critical constraint or capability (e.g., input conversion, translation, or data integrity rules), ensuring that the length is warranted by the value delivered.

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 weak input schema, the description provides most of the necessary context regarding the creation process, data handling, and resulting product (JSON + private link). It defines the 'why' and 'how' of the data conversion and translation.

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?

With low schema coverage (33%), the description acts as a primary documentation source. It explains the purpose of the 'notes' field, the need for content accuracy ('never invent dishes'), and how the 'defaultLanguage' affects the output.

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 specific verb ('Use when the user asks to create'), the resource ('digital or QR menu'), and the output format (JSON). It distinguishes itself by defining the specific function as 'Create' rather than managing an existing menu.

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?

It clearly defines the use case (creating a digital menu for venues) and the intended input source (photo, PDF, or text). It sets boundaries by explicitly stating that images cannot be used as input, steering the agent away from unsupported use cases.

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