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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

set_column_mask

Apply or replace a dynamic data mask on a column in a Microsoft Fabric warehouse or SQL endpoint, supporting default, email, random, and partial masks to protect sensitive data.

Instructions

Apply or replace a dynamic data mask on a column.

Executes ALTER TABLE ... ALTER COLUMN ... ADD MASKED WITH (FUNCTION = '...'). ADD MASKED replaces any existing mask on the column without error.

Blocked by FABRIC_MCP_READONLY.

Supported mask function types:

  • "default" -- full masking; no extra args.

  • "email" -- email masking (exposes first char and ".com" suffix); no extra args.

  • "random" -- numeric random mask; requires start and end.

  • "partial" -- custom string partial mask; requires prefix, padding, and suffix.

Args: workspace: Workspace name or GUID. item: Warehouse or SQL endpoint name or GUID. table_schema: Schema name of the target table. table_name: Name of the target table. column_name: Name of the column to mask. fn_type: Mask function type -- "default", "email", "random", or "partial" (case-insensitive). start: Lower bound for random() masking (required when fn_type is "random"). Must be <= end. end: Upper bound for random() masking (required when fn_type is "random"). prefix: Leading characters to expose for partial() masking (required when fn_type is "partial"). padding: Replacement padding string for partial() masking (required when fn_type is "partial"). Must not contain ", ), ;, --, control characters (including U+0085, U+2028, U+2029), and must not exceed 128 characters. suffix: Trailing characters to expose for partial() masking (required when fn_type is "partial").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNo
itemYes
startNo
prefixNo
suffixNo
fn_typeYes
paddingNo
workspaceYes
table_nameYes
column_nameYes
table_schemaYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description takes full responsibility for behavioral disclosure. It explains the underlying SQL command, the fact that ADD MASKED replaces existing masks, and that it is blocked by READONLY. It also details the mask function types and their parameter requirements. However, it omits potential side effects (e.g., impact on access, reversibility) and error conditions.

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 well-structured: a concise summary line, followed by a clear breakdown of mask function types and a detailed Args section with bullet points. It uses code formatting for emphasis. Every sentence is informative, and the length is justified by the tool's complexity.

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?

Given the high parameter count and presence of an output schema, the description adequately covers the tool's purpose, parameters, and behavioral traits. It could be slightly more complete by mentioning common error scenarios or return value shape, but the output schema likely covers that. Overall, it is sufficiently complete for an agent to invoke correctly.

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?

Schema description coverage is 0%, so the description fully compensates. It provides detailed explanations for all 11 parameters, including required vs optional status, conditional requirements (e.g., start/end for random), and constraints (padding character restrictions, length limits). This adds significant value beyond the schema alone.

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 applies or replaces a dynamic data mask on a column, specifies the SQL command (`ALTER TABLE ... ADD MASKED`), and details the supported mask function types. It effectively distinguishes this from sibling tools like `drop_column_mask` or `list_masked_columns` by its unique action.

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 provides some usage context (e.g., replaces existing mask without error, blocked by READONLY) but does not explicitly guide when to use this tool over alternatives like `drop_column_mask` or `list_masked_columns`. It lacks prerequisite information such as required permissions or schema/table existence.

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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