remove_errors

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states the action (drops rows with error values) and the implementation detail (appends Table.RemoveRowsWithErrors to the M query), which informs the agent about the underlying transformation. It does not discuss edge cases or side effects, but the main behavior is transparent.

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, front-loaded with the core purpose, and every sentence serves a distinct function: stating what it does and explaining parameter usage. There is no wasted 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?

For a relatively simple transformation tool with no output schema, the description covers the essential aspects: purpose, implementation, and column behavior. It does not explain partitionName, but that is documented in the schema. The note about appending to the M query provides useful context about the model-changing nature of the operation.

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 50%, and the description compensates for the columns parameter by explaining its two modes (test only specified columns vs. whole row). However, it does not add meaning for the table or sessionId parameters, which remain undocumented in both schema and description. The description adds marginal value over the schema for columns but does not fully cover the parameter space.

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 uses a specific verb and resource ('drop rows that carry an error value') and explicitly names the underlying M function (Table.RemoveRowsWithErrors). This clearly distinguishes it from siblings like keep_errors and replace_errors by stating 'Remove Errors' as the operation.

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 gives clear context for using the columns parameter ('Pass columns (comma-separated) to test only those columns; omit to test the whole row'), explaining both modes of operation. However, it does not explicitly state when to use this tool vs alternatives like keep_errors or replace_errors, only implying that it is for removing error rows.

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