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HorizunGroup

Horizun PBI MCP

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by HorizunGroup

pbi_open_and_refresh

Destructive

Opens a Power BI Desktop project and refreshes its data in a single call, saving time by combining two steps and ensuring the model has data immediately.

Instructions

Abre el proyecto en Power BI Desktop y lo refresca, en una llamada.

Es la secuencia real de trabajo y siempre eran dos llamadas de unos catorce segundos cada una, porque un .pbip recien abierto trae el modelo SIN DATOS: abrirlo sin refrescar no sirve para comprobar nada.

Devuelve lo mismo que las dos por separado, incluido rows_by_table. Si el archivo ya estaba abierto se reutiliza esa sesion (reuse_open).

Si el refresh falla, la ventana se DEJA ABIERTA: ya cargo bien, y cerrarla borraria justo el contexto que hace falta para ver por que fallo. Sale en desktop_left_open.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
typeNofull
tablesNo
timeoutNo
request_idNo
reuse_openNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the destructiveHint annotation, the description discloses important behavior: if the refresh fails, the window is intentionally left open to preserve context, and this is surfaced via desktop_left_open. It also explains session reuse with reuse_open. No contradiction with annotations.

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 organized into three short paragraphs, front-loading the main purpose. Each sentence adds context (why combined, failure behavior, reuse). It is slightly verbose but justified by the complexity of the operation.

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?

The description covers key behavioral edge cases (failure handling, session reuse) and why this tool exists as a combined operation. An output schema exists, so return values are covered. It could further explain how parameters like type and tables affect the refresh, but the defaults and schema soften this gap.

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 description coverage is 0%, so the description must compensate. It explicitly explains reuse_open (reuse session) and references rows_by_table in output, but does not clarify path, type, tables, timeout, or request_id. Given six parameters, this is insufficient.

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 opens a project in Power BI Desktop and refreshes it in a single call. It also explains why this combined operation is needed (a newly opened .pbip has no data), distinguishing it from separate open-only or refresh-only sibling tools.

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 implies when to use this tool: it's the real work sequence, emphasizing that opening without refreshing is useless. It also mentions reuse_open for already-open sessions. However, it does not explicitly name alternatives like pbi_open_in_desktop or pbi_refresh_model as exclusions, though the context is clear.

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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