List Power BI relationships, including tables, columns, cardinality, cross-filter direction, and status, to reveal model dependencies.
Lista relaciones: tablas/columnas, cardinalidad, filtro cruzado y estado.
| Name | Required | Description | Default |
|---|---|---|---|
| source | No | live |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.0.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds useful context about the output content (tables/columns, cardinality, cross-filter, status), which helps set expectations. However, it doesn't disclose behavior regarding the 'source' parameter or potential limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the main action and lists the key output aspects without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and has an output schema, so return values are covered. The description adequately covers the main functionality but leaves the 'source' parameter unexplained and doesn't position the tool within the broader model inspection workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description completely ignores the single 'source' parameter. With 0% schema description coverage and no explanation in the description, the agent has no information about this parameter's purpose, allowed values, or effect on results.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists relationships and specifies the key attributes included (tables/columns, cardinality, cross-filter, status). This directly differentiates it from sibling list tools like pbi_list_tables and pbi_list_measures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The name implies the purpose, but the description lacks explicit context, prerequisites, or comparisons to other list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.