powerbi-desktop-mcp

check_relationship_integrity

Counts unmatched key values in Power BI relationships to expose rows hidden under (Blank) and totals that stop matching cross-filtered measures, flagging one-to-one and many-to-many issues.

Instructions

For every relationship, count key values with no match on the other side. On many-to-one lookups these are rows that show under (Blank) and vanish from cross-filtered measures -- totals stop matching with no error. One-to-one/many-to-many are flagged only when unmatched from both sides (wrong columns or a data-type/format mismatch).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "instance": "<instance>"
    },
    "name": "check_relationship_integrity"
  }
}

Input Schema

Name	Required	Description	Default
`instance`	Yes
`max_relationships`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 23, 2026

TDQS

B3/5.0

Behavior3/5

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

With no annotations, the description carries full burden, and it does explain the detection logic: many-to-one flagged on one-sided misses, one-to-one/many-to-many only when unmatched on both sides. It omits whether the tool is read-only (implicit from the nature of a check), how expensive the scan is, and what happens when the relationship list exceeds the default cap of 60.

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?

Three tight sentences, front-loaded with the core computation and followed by the failure mode it detects. Dense but every clause adds diagnostic meaning; only the parenthetical about wrong columns is slightly compressed.

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?

An output schema exists, so return-value explanation is not required. However, for a two-param tool with zero schema coverage, the description should at least note the instance scope and the relationship cap; the absence of the truncation behavior is a real gap for correct interpretation of results.

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% across two parameters, and the description never mentions either one. The 'instance' parameter and especially 'max_relationships' (default 60, which silently truncates scope) are undocumented anywhere, so an agent cannot know that coverage may be incomplete.

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 names a specific operation: counting key values on each relationship side that have no match on the other, which tells an agent exactly what the tool computes. It stops short of distinguishing itself by name from the sibling analyze_relationships, leaving the agent to infer which of the two relationship tools to call.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this instead of analyze_relationships or list_relationships, nor any stated prerequisites. The symptom-oriented framing ('totals stop matching with no error') implies a diagnostic use case, but the agent must infer the routing decision.

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