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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

create_security_policy

Create row-level security policies in Fabric Data Warehouse by defining FILTER predicates with schema, function, and target table details.

Instructions

Create a row-level security policy.

Executes CREATE SECURITY POLICY with one or more FILTER predicates. There is no predicate-type option (#966): Fabric Data Warehouse supports FILTER predicates only. Each entry in predicates must include:

  • fn_schema: schema of the predicate function

  • fn_name: name of the predicate function

  • fn_args: list of column names to pass to the function

  • table_schema: schema of the target table

  • table_name: name of the target table

Args: workspace: Workspace name or GUID. item: Warehouse or SQL endpoint name or GUID. policy_name: Qualified policy name ("schema.name" or "name"). predicates: List of predicate definitions (see above). state: Initial policy state -- True to enable, False to disable (default: True).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYes
stateNo
workspaceYes
predicatesYes
policy_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so the description carries full burden. It details the SQL operation, predicate requirements, and state parameter behavior. However, it does not disclose permission requirements or consequences of creating duplicate policies.

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?

Well-structured: one-line summary, predicate details, then argument list. Front-loaded with the action. Slightly verbose but every sentence is informative.

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 output schema exists, return values are covered. The description explains the creation process well, but misses edge cases like duplicate policy names and fails to explicitly mention Fabric Data Warehouse context.

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 coverage is 0%, so the description fully compensates by explaining each parameter: workspace, item, policy_name, predicates (with required subfields), and state (boolean with default). Adds significant value 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 clearly states it creates a row-level security policy using 'CREATE SECURITY POLICY'. It specifies the predicate type limitation (FILTER only) and the required fields. This distinguishes it from siblings like add_security_predicate and set_security_policy_state.

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 explains when to use the tool (to create a new policy) and provides detailed parameter structure. It implicitly differentiates from siblings, but lacks explicit exclusions or when-not-to-use guidance.

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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