add_calculated_field

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

With no annotations provided, the description bears full responsibility for disclosing behavioral traits. The description lacks details about whether the operation is reversible, what side effects occur (e.g., updating the datasource), any authorization requirements, or the response format. Although there is an output schema, the description does not indicate the nature of the output.

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 a single sentence, which is concise. However, it lacks structure (e.g., bullet points or sections) that could improve readability for a multi-parameter tool. It is front-loaded with the key action and resource.

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 complexity (6 parameters, 2 required, no schema descriptions, no annotations), the description is incomplete. It does not explain the return value (though output schema exists), the behavior of the tool, or how parameters interact. The agent would have limited understanding of how to use it 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?

The input schema has 6 parameters with 0% description coverage, meaning the schema provides no descriptions for the parameters. The tool description does not elaborate on any parameters, such as what 'role', 'field_type', or 'default_format' mean. The agent would have to infer meaning from parameter names alone, which is insufficient.

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 action ('Add') and the resource ('calculated field') and specifies it is added to a 'datasource'. However, it does not differentiate from sibling tools like 'add_parameter' or 'add_worksheet' which also add entities, but the resource is distinct enough for an AI agent to infer the purpose.

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?

No guidance is provided on when to use this tool versus alternatives such as 'add_parameter' or 'add_dashboard'. There is no mention of prerequisites, such as needing an existing datasource, or when not to use it.

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