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xlide-excel-word-powerpoint-access-office-vba-mcp

Data validation

xlide_manage_validation
DestructiveIdempotent

List, add, or clear data validation rules in Excel to control cell input and create dropdowns.

Instructions

Lists, adds or clears data validation: what a cell will accept, and the dropdown it shows. kind='list' with formula1 as a comma-separated set of values gives a dropdown; kind='list' with a range reference gives one driven by cells. The other kinds take an operator and one or two formulas, which may be literals or references. Validation stops typing in Excel, not writing through this server, and Excel does not re-check cells that already held a value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNowhole, decimal, list, date, time, textLength or custom.list
sheetYesWorksheet name, matched without case.
actionNolist, add or clear.list
formula1NoThe allowed values. For kind='list', either 'Red,Green,Blue' or a range like $H$1:$H$9. For the others, the bound, such as 0.
formula2NoThe second bound, for between and notBetween.
operatorNobetween, greaterThan, lessThan and so on.between
file_pathYesAbsolute path to the Excel file.
cell_rangeNoFor add and clear: the range. Empty clears the whole sheet.
allow_blankNoLet the cell be left empty.
error_messageNoWhat Excel says when the entry is refused.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already mark this as destructive and not read-only. The description adds valuable behavior beyond annotations: validation is not enforced by the server, and Excel will not re-check cells that already contained a value. This is exactly the kind of side-effect nuance an agent needs.

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 front-loaded with the core purpose and every sentence earns its place by explaining selection behavior, formula semantics, or the server/Excel distinction. It is slightly dense but not bloated.

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?

Given the tool's complexity, the 100%-covered schema, and the presence of an output schema plus annotations, the description is complete. It covers the action variety, dropdown semantics, non-list kinds, and the key Excel/server behavior without needing to restate parameter catalogs or return formats.

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 description coverage is 100%, so the baseline is 3. The description adds extra meaning by explaining that kind='list' with comma-separated formula1 produces a dropdown, while a range reference drives it from cells, and other kinds rely on operator plus formulas. This clarifies relationships between parameters beyond the schema.

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 names a specific resource (data validation) and the exact verbs 'Lists, adds or clears', immediately distinguishing it from sibling tools like xlide_manage_conditional_format and xlide_manage_hyperlink. It also clarifies the dropdown behavior, leaving no ambiguity about what the tool operates on.

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 gives clear context for when to use data validation and provides internal guidance on choosing kind='list' with inline values versus a range, plus the operator/formula pattern for other kinds. It does not explicitly name alternatives, but the resource focus makes the tool choice clear.

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