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excel_write_cell

Write a single value to a specified cell in an existing .xlsx file. Values beginning with '=' are stored as formulas.

Instructions

Write a single value to one cell.

Strings starting with = are persisted as formulas (VAL-EXCEL-022). Other types (int, float, bool, None) are written verbatim via :meth:openpyxl.cell.Cell.value.

Args: path: Path to an existing .xlsx. sheet: Name of the sheet. cell: A single cell reference like "A1". value: Value to write. folder: Optional base folder for relative paths.

Returns: {"ok": True}.

Raises: OfficeMCPError: ERR_FILE_NOT_FOUND if the file is missing, ERR_SHEET_NOT_FOUND for an unknown sheet, ERR_CELL_PARSE for a malformed cell, ERR_UNSUPPORTED_FMT for non-.xlsx extensions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
sheetYes
cellYes
valueYes
folderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses behavior: formula handling (strings starting with '='), type handling (int, float, bool, None), error cases (ERR_FILE_NOT_FOUND, etc.), and return value. This is comprehensive.

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 a clear opening sentence followed by Args, Returns, and Raises sections. While informative, it is slightly verbose due to exhaustive error documentation, but every sentence adds value.

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

Completeness5/5

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

The description covers all necessary context: what the tool does, parameter details, return value, and error conditions. Although an output schema exists (not shown), the description adequately describes the return format. No gaps remain.

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?

Despite 0% schema description coverage, the description's Args section explains each parameter's purpose and constraints. It clarifies that 'value' supports multiple types and that 'folder' is optional. This compensates fully for the schema gap.

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 it writes a single value to one cell. It distinguishes itself from sibling tools like 'excel_write_range' by specifically targeting single cell operations. The verb 'write' and resource 'single cell' are precise.

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 implies use for single cell writes, but does not explicitly state when to use this tool versus alternatives like 'excel_write_range'. No exclusion or when-not-to-use guidance is provided.

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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