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pbi_validate_relationship_plan

Prevent data model errors by validating relationship cardinality, direction, duplicates, and ambiguity before creation in Power BI.

Instructions

Validate relationship cardinality, direction, duplicates, and ambiguity before creation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
to_tableYes
directionNooneDirection
is_activeNo
to_columnYes
from_tableYes
cardinalityNooneToMany
from_columnYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only mentions validation aspects but does not state that the tool is read-only, what the output looks like, or any prerequisites (e.g., existing tables/columns). The description is insufficient to fully understand the tool's behavioral traits.

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 sentence with no wasted words. It is concise but could benefit from a slightly more structured breakdown of the validation checks. Still, it is appropriately sized for the content.

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 7 parameters and 4 required, the description is too brief. It does not explain what 'ambiguity' or 'duplicates' refer to, nor what the output schema contains. The existence of an output schema is assumed but not leveraged. The description lacks key details for a comprehensive understanding.

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 coverage is 0%, so the description must compensate. It mentions cardinality, direction, duplicates, and ambiguity, which map to some parameters, but does not explain parameters like 'is_active' or provide details on format or allowed values. The description adds minimal 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 validates relationship cardinality, direction, duplicates, and ambiguity before creation. It uses a specific verb 'Validate' and resource 'relationship plan', distinguishing it from sibling tools like pbi_create_relationship and pbi_update_relationship.

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 phrase 'before creation' implies it should be used to validate a proposed relationship, but there is no explicit guidance on when to use it vs. alternatives, what prerequisites are needed, or what constitutes a valid plan. The usage context is implied but not fully explicit.

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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