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Remove Validation

remove_validation
Destructive

Remove Excel data validation from a range, freeing cells from input restrictions. Specify workbook, sheet, and A1 address.

Instructions

Remove data validation from a range.

Args: workbook: Workbook name or path (None = active workbook). sheet: Worksheet name (None = active sheet). range_address: A1-style address, e.g. "B2:B20".

Returns: JSON confirmation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sheetNo
workbookNo
range_addressNoA1
Behavior3/5

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

The annotations declare destructiveHint: true, which the description does not contradict. The description adds minimal behavioral detail beyond that, such as the return of JSON confirmation, but does not describe side effects or irreversibility. It does clarify default behaviors for workbook and sheet, which is useful but not behavioral transparency per se.

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 concise and well-structured, with the action stated upfront followed by a clear args/returns format. Every sentence adds value without redundancy.

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?

For a simple removal tool, the description covers the core essentials: what it does, parameters, and return type. However, it omits details like whether it only affects existing validation or what happens if no validation exists. Given the tool's simplicity and the presence of annotations, this is a minor gap.

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?

The description provides meaningful explanations for all three parameters, including defaults and an example for range_address. Since the schema provides no descriptions (0% coverage), the description fully compensates, making parameter semantics clear.

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 action (remove) and the target (data validation from a range). It is distinct from sibling tools like add_dropdown_validation and get_validation. The purpose is 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 does not explicitly mention when to use this tool versus alternatives like add_validation or clear_range. The usage is implied by the name and action, but there is no explicit guidance on selection criteria.

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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