Aspose.Cells Cloud MCP Server

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Remove Symbols

remove_symbols

Remove all symbol and special characters from cells in a specified worksheet range, preserving letters, numbers, and spaces.

Instructions

Removes all symbol and special characters (punctuation, currency symbols, mathematical operators, etc.) from cells within a specified range of a worksheet in an Excel file using Aspose.Cells Cloud API, preserving alphanumeric characters (A-Z, a-z, 0-9) and whitespace. Returns True if the operation succeeds.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`_range`	No
`file_uuid`	Yes
`worksheet`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv26.4.1Sep 18, 2026
- removedInput schema / properties / file_token
```
Removed value: -{
-  "type": "string"
-}
```
- addedInput schema / properties / file_uuid
```
Added value: +{
+  "type": "string"
+}
```
- changedInput schema / required
```
Previous value: -[
-  "file_token"
-]New value: +[
+  "file_uuid"
+]
```
First observedv26.4.0Aug 1, 2026

TDQS

C2.9/5.0

Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It does add useful details like preserving alphanumeric characters and returning True on success, but it omits critical side-effect information: it does not state whether the Excel file is modified in place, whether permissions are required, or what happens when no range is provided. This is a significant gap for a mutating operation.

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 a single compact sentence that front-loads the primary action and includes a helpful preservation rule. It is not overly verbose, though the parenthetical list of character types is slightly redundant. Overall it is well-structured and readable.

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

Completeness2/5

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

For a tool with three parameters, no schema-level parameter descriptions, no annotations, and many similar sibling tools, this description is incomplete. It does not explain optional parameter behavior, distinguish what happens with a null range, or describe the output schema despite one being present. An agent would need more context to invoke it correctly with confidence.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It vaguely references 'specified range' and 'worksheet', which map to _range and worksheet, and implies file_uuid identifies the file, but it does not explain accepted formats, defaults (e.g., null _range), or why only file_uuid is required. The parameter semantics are incomplete.

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 verb 'Removes', the resource ('cells within a specified range of a worksheet in an Excel file'), and the exact scope of characters (symbols and special characters, preserving alphanumeric and whitespace). This distinguishes it from sibling tools like remove_numeric_characters or remove_punctuation_marks by covering a broader set of non-alphanumeric characters.

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

Usage Guidelines2/5

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

The description gives no explicit instructions on when to choose this tool over alternatives such as remove_punctuation_marks or remove_non_printing_characters. It defines the operation but does not state conditions, exclusions, or a recommended selection path among the many sibling text-removal tools.

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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