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

The description discloses a crucial behavioral constraint: 'if there is one.' This informs the agent that the tool may return no data if no analysis has been written for the assessment, which is valuable context not provided by the readOnly/destructive hints in the 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 extremely brief and front-loaded, capturing the core function and the essential edge case (existence) in a highly concise manner without any filler.

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 simplicity of the input (1 parameter) and the high clarity of the purpose, the description is functionally complete for triggering the tool. It only lacks detail on the format of the analysis, which would typically be found in an output schema.

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?

Since schema description coverage is 100%, the parameters are well-documented by the schema itself. The description does not add specific meaning or nuance to the 'assessmentId' beyond confirming it refers to the ID of a specific assessment.

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 defines the function (retrieving AI analysis) and the target object (an assessment). While the name is highly specific, the description adds a layer of intent by specifying the 'AI analysis' aspect, making it clear what kind of data is returned compared to general assessment data.

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 definition offers almost no usage guidelines. It does not tell the agent when to choose this tool over general tools like 'get_assessment' or when the analysis is actually expected to exist, leaving the agent to rely solely on execution and error handling.

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