set_table_detail_rows

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

With no annotations, the description carries the burden of behavioral disclosure. It does explain the semantic effect: it sets the default detail rows definition used when drilling into a table value with no per-measure rows. It also clarifies that daxTableExpression is a DAX table expression. However, it doesn't mention side effects like overwriting existing definitions, permissions, or error conditions, which would be helpful for a mutation tool.

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 relatively concise at two sentences, front-loaded with the primary action. The inclusion of the distinct sibling and the explanatory clause about drilling is efficient. The final clause 'daxTableExpression is a DAX table expression' is slightly redundant with the schema, but overall the structure is acceptable.

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 simple setter tool with no output schema, the description is fairly complete. It explains the purpose, the specific scenario in which the default applies, and the key parameter expression. It doesn't explain return values (not needed) or prerequisites like session validity, but such details are less critical for this type of 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 only 33% (only daxTableExpression has a description). The description mainly repeats that 'daxTableExpression is a DAX table expression' which adds no value beyond the schema. It does not explain 'sessionId' or 'table' parameters, leaving the agent to infer their meaning from names alone. This is a gap given the low schema coverage.

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's action: 'Set a TABLE's default detail rows (Table.DefaultDetailRowsDefinition)'. It specifies the resource (TABLE) and the specific property being set. It also distinguishes itself from the sibling tool set_detail_rows by calling out 'Distinct from the measure-level set_detail_rows', making its scope unambiguous.

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 provides clear context for when to use this tool: 'the DAX table returned when a user drills into a value of this table that has no per-measure detail rows'. It also names the alternative set_detail_rows for measure-level detail rows, which gives an explicit alternative. However, it doesn't fully state 'when not to use' in absolute terms, only implying it via the distinction.

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