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diff_models

Compare two Power BI semantic models or PBIP snapshots to identify added, removed, and modified tables, columns, measures, and relationships across branches or releases.

Instructions

Compare two semantic models and report structural differences.

Use this tool when the user asks to:

  • Compare two versions of a Power BI model or PBIP directory.

  • See what tables, columns, measures, or relationships changed between branches or releases.

Args: before: Path to the baseline PBIP directory or snapshot. after: Path to the target PBIP directory or snapshot. inspector: Optional model inspector callable.

Returns: Dict detailing added, removed, and modified tables, columns, measures, and relationships.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterYes
beforeYes
inspectorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the comparison inputs and the return shape (added/removed/modified tables, columns, measures, relationships), but never states that the operation is non-mutating or what permissions/paths are required.

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 purpose sentence followed by structured usage bullets, Args, and Returns. Well-organized and every section earns its place, though the Returns section is slightly redundant given an output schema exists.

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?

Covers purpose, usage, all three parameters, and the return structure. An output schema exists so return values needn't be explained, but the extra description is harmless and the definition is complete enough to invoke correctly.

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 coverage is 0%, so the description must compensate. It does: 'before' is the baseline and 'after' the target PBIP directory or snapshot, and 'inspector' is documented as an optional model inspector callable, giving real meaning beyond the bare string/any schema.

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?

States a specific verb and resource: 'Compare two semantic models and report structural differences.' The purpose is unambiguous and no sibling tool performs a diff, so an agent can select it confidently.

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 explicit triggering contexts via 'Use this tool when the user asks to: compare two versions... see what changed between branches or releases.' Clear positive guidance, though it names no alternatives or when-not conditions.

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