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excel_create_pivot_table

Destructive

Generate a pivot table from specified data range in an Excel file to summarize and analyze data with row, column, and value fields.

Instructions

Create a pivot table for data analysis

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYesPath to the Excel file
sourceSheetNameYesSource sheet name
sourceRangeYesSource data range
targetSheetNameYesTarget sheet for pivot table
targetCellYesTarget cell (e.g., A1)
rowsYesRow fields
columnsNoColumn fields
valuesYesValue fields with aggregation
createBackupNo
Behavior2/5

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

The annotation indicates destructiveHint: true, but the description does not add behavioral context beyond creating a pivot table. It does not disclose that the workbook file is modified, or mention potential impacts like overwriting existing data. Description adds minimal value beyond the annotation.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it is too minimal given the complexity of pivot table creation. It lacks structure and does not adequately convey key aspects. Could be more informative while remaining concise.

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

Completeness2/5

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

Given the tool has 9 parameters (7 required) and no output schema, the description is incomplete. It does not explain how pivot tables work, how aggregation is specified, or how rows/columns/values interact. An AI agent would need more context to invoke this correctly.

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

Parameters3/5

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

Schema description coverage is 89%, so most parameters have descriptions in the schema. The description does not provide additional semantic meaning for parameters (e.g., how 'values' with aggregation works). With high coverage, baseline 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool creates a pivot table for data analysis. It distinguishes from sibling tools like excel_create_chart, excel_create_table, etc., as a pivot table operation. However, it lacks specificity about pivot table capabilities (e.g., aggregation, layout).

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs alternatives. Does not mention prerequisites (e.g., source data must be structured) or when it's appropriate (e.g., summarizing large datasets). No exclusion criteria or context of use.

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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