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excel_get_info

Retrieve a summary of sheets in an Excel workbook, including name, index, row count, and column count.

Instructions

Return a summary of the workbook's sheets and sizes.

The returned dict contains:

  • path — absolute path of the file on disk.

  • sheets — list of one dict per sheet, in insertion order. Each entry has name (str), index (int, 0-based), rows (int, openpyxl's max_row), and cols (int, openpyxl's max_column).

Args: path: Path to an existing .xlsx. folder: Optional base folder for relative paths.

Raises: OfficeMCPError: ERR_FILE_NOT_FOUND if the file is missing, ERR_UNSUPPORTED_FMT for non-.xlsx extensions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
folderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden. It fully discloses the return structure and error types (ERR_FILE_NOT_FOUND, ERR_UNSUPPORTED_FMT). It implies the tool is read-only by describing a summary retrieval, though it does not explicitly state 'read-only' or mention side effects. This is sufficient for clarity, earning a high but not perfect score.

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 well-structured with clear sections (Return structure, Args, Raises). However, it is slightly verbose, especially in the detailed dict layout, which could be shortened without losing clarity. The front-loading of the return type is effective, but the Args part is redundant with the schema.

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 tool's complexity (simple info retrieval), the description covers the return value fully (aided by output schema), parameter semantics, and error conditions. It does not discuss permissions or rate limits, but these are not critical for this tool. The presence of an output schema reduces the burden on the description, making it sufficiently complete.

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

Parameters5/5

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

Schema description coverage is 0%, yet the description adds detailed semantics: 'path' is described as 'Path to an existing .xlsx' and 'folder' as 'Optional base folder for relative paths.' This fully compensates for the schema's lack of descriptions, providing agents with clear guidance on parameter usage beyond the type definition.

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 it returns a summary of the workbook's sheets and sizes. The description specifies the exact structure of the return value and distinguishes it from siblings like excel_list_sheets by focusing on comprehensive sheet metadata. It uses specific verbs and resources, making the tool's purpose unambiguous.

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

Usage Guidelines3/5

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

The description implicitly explains when to use this tool (to get structured info about all sheets), but it does not explicitly contrast with alternatives such as excel_list_sheets or excel_read_sheet. No 'when not to use' or alternative recommendations are provided, leaving the agent to infer context from sibling names.

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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