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remove_duplicates

Remove duplicate rows or duplicate values in specific columns from a Power BI table by adding Table.Distinct to the M query. Keep one row per unique combination.

Instructions

Power Query Remove Duplicates: keep one row per distinct combination. Appends Table.Distinct to the table's M query. Pass columns (comma-separated) to dedupe on those columns only; omit to dedupe whole rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
columnsNocolumns to dedupe on, comma-separated (omit for whole-row distinct)
sessionIdYes
partitionNameNopartition name (optional; defaults to the first partition)
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It adds useful behavioral context by stating 'Appends Table.Distinct to the table's M query,' which reveals the underlying transformation. However, it does not disclose potential side effects, reversibility, or whether the operation modifies state in a way that could affect other parts of the model.

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 two sentences long and front-loaded with the primary purpose ('keep one row per distinct combination') followed by essential usage detail. Every sentence contributes meaning, and there is no redundant or filler content.

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

Completeness4/5

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

Given the simplicity of this transformation tool, the description covers the core behavior and configuration options. It does not mention return values or error conditions, but with no output schema and standard parameters like sessionId and partitionName, the description is adequate for an agent to use the tool correctly in most cases.

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 documents the 'columns' parameter with the same wording ('columns to dedupe on, comma-separated (omit for whole-row distinct)'), so the description adds no new meaning for that parameter. The 'table' and 'sessionId' parameters are not explained in either the schema or the description, and with 50% schema coverage, the description does not compensate for the lack of documentation.

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 purpose: 'Remove Duplicates: keep one row per distinct combination.' It specifies the resource (table) and the operation (appending Table.Distinct to the M query), making it easy to distinguish from sibling tools like remove_alternate_rows or remove_blank_rows.

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

Usage Guidelines4/5

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

The description provides clear usage context: 'Pass columns (comma-separated) to dedupe on those columns only; omit to dedupe whole rows.' It explains the two modes of operation but does not explicitly mention alternatives or when not to use this tool, so it falls short of a 5.

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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