powerbi-orchestrator-mcp

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audit_model_and_report

Audit Power BI projects (.pbip) for compliance with best practice rules, DAX quality, naming conventions, and WCAG 2.1 accessibility. Returns score and findings.

Instructions

Composite quality and compliance audit on a Power BI project (PBIP).

Use this tool when the user asks to:

Audit, inspect, or validate a Power BI project (.pbip) or semantic model.
Check Best Practice Analyzer (BPA) rules, DAX code quality, or naming conventions.
Validate WCAG 2.1 accessibility (contrast, missing alt text, chart readability).

Args: pbip_path: Path to the root .pbip directory or folder. bpa_ruleset: Best practice ruleset to run ("default", "strict", "lenient"). dax_measures_json: Optional JSON string or dictionary mapping measure names to DAX expressions. bpa: Whether to execute Tabular BPA checks. dax_lint: Whether to execute static DAX linting checks. accessibility: Whether to audit WCAG 2.1 accessibility on report pages. naming: Whether to validate column, measure, and table naming conventions.

Returns: Dict with overall score (0-100), pass/fail status, and categorized findings.

Input Schema

TableJSON Schema

Name	Required	Default
`bpa`	No
`naming`	No
`dax_lint`	No
`pbip_path`	Yes
`bpa_ruleset`	No	default
`accessibility`	No
`dax_measures_json`	No	{}

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.11.0Oct 2, 2026
- removedInput schema / properties / dax_measures_json / type
```
Removed value: -"string"
```
First observedv0.1.0Sep 10, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that the audit is composite and that bpa/dax_lint/accessibility/naming are individually switchable, and that it returns a score/pass-fail with categorized findings. It does not state whether the operation is read-only, what permissions or runtime cost it incurs, or how the sub-checks interact.

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?

Front-loaded with the core purpose, then structured Usage/Args/Returns sections with no filler. The Returns block is partly redundant given an output schema exists, but the overall structure is efficient and scannable.

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?

For a 7-parameter, no-annotation tool with an output schema, it covers purpose, triggers, and every argument. The gaps are minor: no read-only/side-effect note and no interaction guidance among the boolean toggles.

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

Parameters4/5

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, and it does: all seven parameters are named and explained, including the bpa_ruleset enum values (default/strict/lenient) and the optional dax_measures_json. It omits declared defaults and how dax_lint interacts with dax_measures_json, so not a full 5.

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?

States a specific verb (audit) and resource (Power BI PBIP project / semantic model / report) and enumerates the concrete dimensions checked: BPA rules, DAX quality, naming, WCAG accessibility. It does not explicitly differentiate itself from close siblings like audit_report_ux_and_storytelling or powerbi_health, so it stops short of a 5.

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?

Provides a clear 'Use this tool when the user asks to:' trigger list covering audit, BPA/DAX/naming, and WCAG validation, which gives an agent solid routing signal. However, it names no alternatives or when-not-to-use conditions against the many overlapping siblings.

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