Aspose.Cells Cloud MCP Server

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Remove Numeric Characters

remove_numeric_characters

Strip all numeric digits (0-9) from cells in a specified Excel worksheet range, leaving letters, symbols, and spaces intact. Ideal for cleaning alphanumeric data without altering non-numeric content.

Instructions

Removes all numeric digit characters (0-9) from cells within a specified range of a worksheet in an Excel file using Aspose.Cells Cloud API, preserving letters, symbols, 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

B3.3/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It does disclose the core behavior, the characters removed, and the return value ('Returns True if the operation succeeds'). However, it does not state whether the operation overwrites the file in-place, whether it is reversible, or any permission/rate-limit implications.

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?

Two concise sentences, front-loaded with the primary action and scope. The preservation detail and return-value note both earn their place; there is no filler or repetition.

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?

Given 0% schema coverage and no annotations, the optional _range and worksheet parameters are ambiguous: an agent cannot tell whether omitting them means 'whole worksheet' or 'whole workbook' or what range format is expected. The output schema may cover the return shape, but the invocation context for a non-trivial Excel mutation is under-specified.

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, but it does not explain the parameters at the schema level. It loosely references a worksheet and range, but never names file_uuid, _range, or worksheet, nor explains what null defaults mean. This leaves the agent without enough semantic grounding for the required and optional parameters.

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 operation ('Removes all numeric digit characters'), a concrete resource (cells in a worksheet range of an Excel file), and explicitly states what is preserved. This makes it clearly distinguishable from sibling tools like remove_symbols or remove_text_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?

No guidance is given on when to use this tool versus the many similar sibling tools (remove_symbols, remove_non_printing_characters, remove_custom_characters, etc.). There are no explicit exclusions, prerequisites, or alternative-selection cues, so the agent must infer usage from the tool name alone.

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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