Skip to main content
Glama

list_sheets

Retrieve all sheet names, dimensions, and metadata from an Excel workbook to understand its structure before reading contents.

Instructions

List all sheets in an Excel workbook with their dimensions and metadata.

Returns sheet names, row/column counts, data ranges, merged cell counts, and total embedded image count. Use this to understand the structure of an Excel file before reading its contents.

@param file_path: Absolute path to the .xlsx file. @return: Formatted text with workbook structure overview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Without annotations, the description carries full burden. It lists what is returned: 'sheet names, row/column counts, data ranges, merged cell counts, and total embedded image count.' It doesn't discuss side effects or permissions, but as a read-only listing, this is sufficient. The behavior is transparent.

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 three sentences plus a parameter note, all front-loaded with the primary action. Every sentence adds value, no redundancy. It is concise and well-structured.

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 that there is an output schema (context indicates 'Has output schema: true'), the description doesn't need to fully detail return values but does summarize them. The tool is simple with one required param, and the description provides enough context for an agent to use it effectively. Minor gap: no mention of error conditions or file existence checks.

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

Parameters4/5

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

Schema coverage is 0%, so the description must document parameters. It explicitly describes the only parameter 'file_path' as 'Absolute path to the .xlsx file.' This adds meaning beyond the schema's type and title. It could include examples but is adequate.

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 action: 'List all sheets in an Excel workbook with their dimensions and metadata.' It specifies the resource (sheets in a workbook) and the verb (list). The description distinguishes from siblings like 'read_excel_data' by explicitly mentioning it's for understanding structure before reading content.

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 a clear usage guideline: 'Use this to understand the structure of an Excel file before reading its contents.' This implies when to use (before reading tools) but does not explicitly mention when not to use or list alternative tools. However, the context makes it helpful.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/VOYAGER-Inc/excel-vision-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server