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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

list_sql_permissions

List T-SQL database permissions by workspace and item, with optional filtering by principal, schema, or object name. Returns securables for database, schema, and object classes.

Instructions

List T-SQL database permissions from sys.database_permissions.

Reads from sys.database_permissions joined to sys.database_principals. Returns DATABASE, SCHEMA, and OBJECT class securables with readable names.

Args: workspace: Workspace name or GUID. item: Warehouse or SQL endpoint name or GUID. principal: Filter by principal name (optional). schema: Filter by schema name -- returns SCHEMA class rows for this schema (optional). object_name: Filter by qualified object name <schema>.<object> -- returns OBJECT class rows for this object (optional).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYes
schemaNo
principalNo
workspaceYes
object_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It describes reading from system views but does not explicitly state it is read-only or that no modifications occur. It also does not disclose permission requirements or rate limits. However, the description does reveal the data source and return classes.

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: a brief introductory sentence followed by a structured Args list. Every sentence is purposeful, with no redundancy. The main action is stated upfront, and optional parameters are clearly separated.

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 tool's moderate complexity (5 parameters, no annotations, but presence of output schema), the description covers the purpose, data source, return classes, and optional filters. It could explicitly mention the read-only nature, but overall it provides sufficient context for an AI 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 must compensate. It provides clear, human-readable meanings for all 5 parameters, including optional filters for principal, schema (with behavior note), and object_name (with format requirement). This adds substantial value beyond the schema's type-only definitions.

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 lists T-SQL database permissions from sys.database_permissions, specifying the source and scope. It explains it returns DATABASE, SCHEMA, and OBJECT class securables with readable names, distinguishing it from sibling permission tools like grant_permission or list_item_permissions.

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 explicit guidance on when to use this tool versus alternatives. The description does not mention prerequisites, exclusions, or comparative advantages relative to sibling tools like my_permissions or list_item_permissions. Usage context must be inferred.

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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