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senoff

xlsx-for-ai

xlsx_topology

Read-onlyIdempotent

Get a complete workbook overview in one call: sheets, dimensions, formulas, named ranges, tables, validations, hyperlinks, merges, and feature flags. Used to orient before diving deeper.

Instructions

one-call workbook orientation. Returns sheets × dimensions × formulas × named ranges × tables × validations × hyperlinks × merges in one shot, plus feature flags (macros / external refs / pivots / LAMBDA / dynamic arrays). No other tool can do this: pandas gives you a frame per sheet but no structure; openpyxl makes you fan out across 6+ object trees to learn the same thing; this is the "what is in this workbook?" call you make first to decide which other tool to call next.

USE WHEN: an agent has just been handed a workbook and needs to orient before drilling in. Or surveying many workbooks for triage / index. Or auditing whether a workbook is "interesting" (formulas? macros? external refs?). Free tier — counts against the 10k/mo cap.

DO NOT USE WHEN: you already know the sheet you want and just want its data (use xlsx_read or xlsx_describe).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_b64Yes
Behavior4/5

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

Annotations already provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds behavioral context like 'one-call' nature, free tier with 10k/month cap, and the broad scope of what it inspects. 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.

Conciseness4/5

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

The description is a bit long but well-structured: a concise core statement, a comparative paragraph, and clear use/when-not sections. Every sentence adds value, though the list of returned items could be slightly abbreviated.

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 lists what the tool returns but lacks specifics on the output format (e.g., JSON structure). Given no output schema, this is a gap. However, the tool's purpose and usage are well covered, so it's slightly incomplete.

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?

Only one parameter (file_b64) with no schema description coverage. The description does not explain the parameter format, but its purpose is inferable from the tool name and context. Baseline 3 given low coverage but simple parameter.

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 returns a workbook orientation with a detailed list of components (sheets, dimensions, formulas, etc.) and contrasts with siblings like pandas and openpyxl. It explicitly says 'No other tool can do this', making its unique purpose very clear.

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?

The description provides explicit USE WHEN and DO NOT USE WHEN sections, giving clear context for when to use this tool (orientation after receiving a workbook, triage, auditing) and alternatives (xlsx_read, xlsx_describe) when not to use it.

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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