pbi_create_hierarchy

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

With all annotations set to false, the description carries the burden of behavioral disclosure. It reveals that the operation writes TMDL, requires a closed project, and deliberately preserves the order of levels without sorting or deduplication. Missing overwrite behavior and error handling, but the disclosed traits are meaningful and non-obvious.

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 compact and front-loaded: a purpose sentence, a focused parameter note, and a prerequisite. It has no wasted sentences, though the phrase 'porque es informacion' is slightly awkward and could be tightened. Overall, it is concise and well structured.

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 description captures the core invocation requirements: same-table columns, correct level order, and a closed Power BI project. However, with seven parameters and zero schema descriptions, it leaves overwrite semantics and optional fields under-specified. An output schema exists but does not compensate for these parameter knowledge gaps.

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?

Schema description coverage is 0%, so the description must compensate by explaining parameter meanings. It does this only for `levels`, which is richly explained with ordering and preservation semantics. The remaining six parameters—`table`, `name`, `overwrite`, `request_id`, `description`, and `display_folder`—are left to name-based inference, which is insufficient at this coverage level.

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 opens with 'Crea una jerarquia sobre columnas de la misma tabla', which clearly identifies the verb (create) and resource (hierarchy on columns of a table). It does not explicitly distinguish itself from sibling creation tools, but the hierarchy object type is unambiguous enough to avoid confusion with measure or column creation.

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?

The description gives a concrete prerequisite: 'requiere el proyecto CERRADO en Power BI Desktop' and specifies the required ordering of levels from high to low granularity. It does not mention when to choose an alternative tool, but the closed-project requirement and ordering semantics are useful usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.