remove_calculated_field

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

With no annotations provided, the description carries the full burden. It transparently states that the tool refuses to remove data-bound fields and explains why. It could mention if the operation is reversible or any side effects, but the core behavior is well-covered.

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 two sentences long with no wasted words. Every sentence adds essential information: the main action, a refusal condition, and alternatives.

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?

The description adequately covers the core functionality and refusal condition. However, given the lack of parameter descriptions and no output schema, it could be more helpful by explaining parameter roles. Still, it is fairly complete for a removal tool.

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%, yet the description does not explain any parameter meanings. It only implies field_name is the name of the calculated field. path and dataset_name remain unexplained, leaving the agent to infer from context.

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 tool removes a calculated field by name, distinguishing it from data-bound fields. It uses specific verb 'Remove' and resource 'calculated <Field>', which is distinct from sibling tools like remove_dataset_field.

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 explicitly states when to use this tool (for calculated fields) and when not (for data-bound fields). It provides clear alternative tools: remove_dataset_field for data-bound fields and update_dataset_query for rewriting the query.

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