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unpivot_columns

Reshape Power BI data by converting selected columns into attribute-value row pairs. Pass comma-separated column names to append Table.Unpivot.

Instructions

Power Query Unpivot Columns: turn the listed columns into Attribute/Value row pairs. Appends Table.Unpivot to the table's M query. columns is comma-separated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
columnsYescolumns to unpivot, comma-separated
sessionIdYes
partitionNameNopartition name (optional; defaults to the first partition)
Behavior2/5

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

With no annotations provided, the description must carry the burden of behavioral disclosure. It mentions that Table.Unpivot is appended to the M query, which is useful, but it does not disclose side effects such as the original columns being removed or the resulting table structure changes. Lack of safety/reversibility information is a gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences with the purpose front-loaded and no filler. It efficiently conveys the core operation and one key parameter detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core functionality and result shape (Attribute/Value pairs), but it omits important behavioral details like the impact on original columns, whether the operation is reversible, and how the result is returned. Given no output schema and no annotations, this leaves some context gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes 'columns' as comma-separated, and the description repeats that exact info, adding no extra meaning. The description does not explain 'sessionId' or 'table', leaving half of the parameters undocumented despite schema coverage of only 50%.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: turning listed columns into Attribute/Value row pairs via Table.Unpivot. This specific verb+resource+output distinguishes it from sibling tools like unpivot_other_columns, which unpivot all columns except the listed ones.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The use case is implied by the description (unpivot specific columns), but there is no explicit guidance on when to choose this over alternatives like unpivot_other_columns or unpivot_keep_nulls. No exclusions or alternative tool recommendations are provided.

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

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