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HorizunGroup

Horizun PBI MCP

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by HorizunGroup

pbi_audit_model

Read-only

Audit a Power BI semantic model with stable identifier rules, filtering by severity to get evidence-backed findings, recommendations, and auto-fix availability.

Instructions

Audita el modelo semantico con reglas de identificador estable.

Cada hallazgo trae rule, severity, object, evidence, recommendation y auto_fix_available. Ninguna heuristica se presenta como certeza: la evidencia acompana siempre al hallazgo. rules: subconjunto de reglas (ver pbi_list_audit_rules). min_severity: info | warning | error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rulesNo
sourceNolive
min_severityNoinfo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description discloses that each finding includes specific fields and that evidence always accompanies findings, meaning heuristics are not presented as certainty. This goes beyond the readOnlyHint annotation by explaining the epistemic behavior of results.

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?

Three sentences cover purpose, output shape, and core parameters with no filler. Front-loaded with the primary action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The output schema is present and the description covers the main result structure, but the `source` parameter is unexplained and no sibling differentiation is given. For a 3-parameter tool with zero schema descriptions, this leaves some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explains the meaning of `rules` and `min_severity`, including the accepted values for min_severity. The `source` parameter is left undocumented, and with 0% schema coverage, this is a gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Audita el modelo semantico' with a specific verb and resource, clearly identifying the tool's function. However, it does not differentiate from sibling audit tools like pbi_audit_project or pbi_audit_report_only.

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 description references pbi_list_audit_rules for the rules parameter, providing a path to discover valid rules. It does not state when to use this over pbi_audit_project or pbi_audit_report_only, so usage guidance is only implicit.

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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