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xlsx-for-ai

xlsx_pivot_tables

Read-onlyIdempotent

List all pre-existing pivot table definitions in an Excel file, including fields, ranges, and aggregation functions, for auditing or documenting pivot table structures.

Instructions

List every PRE-EXISTING pivot table definition in a LOCAL .xlsx file (the ones an Excel user already built). Per pivot: sheet, name, location range, source range (or named-range / table reference), row / column / page fields, and data fields with their agg function (sum / count / average / max / min / product / stdDev / etc.).

Distinct from xlsx_pivot which COMPUTES a fresh pivot from raw data — this tool surfaces the existing pivot CONTRACT so an agent can answer "what does PivotTable3 on the Summary sheet actually compute?".

USE WHEN: documenting a financial model that uses pivot tables. Or auditing whether a pivot still points at the right source range after a data refactor. Or answering "which sheet aggregates Sales by Region?" without re-deriving it.

DO NOT USE WHEN: you want to COMPUTE a fresh pivot from raw data (use xlsx_pivot). Or you only need cell values (use xlsx_read).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_b64Yes
optionsNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. Description adds behavioral context such as listing only pre-existing pivot definitions and details returned per pivot (sheet, name, location, source, fields, aggregations). No contradictions.

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?

Well-structured with clear sections: main purpose, details of output, distinction from sibling, when/not to use. Every sentence adds value. No wasted words.

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?

Provides detailed information about what data is returned per pivot (sheet, name, location, source, fields, aggregations) and three use cases. Lacks specifics on file type limitations (e.g., .xlsm?) and error handling, but overall sufficient given no output schema.

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 coverage is 0%, so description must compensate. It mentions 'file_b64' implicitly via 'LOCAL .xlsx file' and 'options.sheet' as optional filter. However, it does not explain how to provide the file (e.g., base64 string) or format of options object. Adds some meaning beyond schema but incomplete.

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?

Clearly states verb 'List' and resource 'PRE-EXISTING pivot table definitions in a LOCAL .xlsx file'. Distinguishes from sibling xlsx_pivot by specifying it lists existing definitions rather than computing fresh ones.

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

Usage Guidelines5/5

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

Explicitly provides when to use: documenting financial models, auditing source ranges, answering aggregation questions. Also provides DO NOT USE cases with specific alternative tool names (xlsx_pivot, xlsx_read).

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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