transform_all_column_names

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

No annotations are provided; the description carries the burden. It discloses the side-effect of appending a step to the M query, which is useful, but does not explain potential naming collisions or return values.

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?

Two sentences front-loaded with the core action and transform list; no redundant wording.

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 tool has 5 parameters and no output schema; the description covers the transform semantics and side-effect but leaves out return value details and does not mention the partitionName parameter, which is only in the 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?

The description explains each transform option (e.g., snakeToSpace, camelSplit) and notes that prefix requires an arg, adding meaning beyond the schema's simple enum list. It also clarifies the arg parameter's role.

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 bulk-transforms every column name via Table.TransformColumnNames, listing available transformations. This specific verb+resource scope distinguishes it from sibling column-rename tools.

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 phrase 'Bulk-transform every column NAME' provides clear context for when to use this tool, though it does not explicitly name alternatives or exclusion cases.

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