powerbi-desktop-mcp

check_refresh_dependencies

Analyze Power BI query dependencies to identify which tables fail if sources are unreachable, detect circular references, orphan queries, and high fan-out staging steps before refresh.

Instructions

The query dependency graph: what feeds what, chain depth, which loaded tables fail if each source (SQL server / SharePoint site) is unreachable, high fan-out staging queries, orphan queries nothing uses, parameters and their consumers, circular references.

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_refresh_dependencies"
  }
}

Input Schema

Name	Required	Description	Default
`instance`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 23, 2026

TDQS

C2.6/5.0

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 usefully discloses the kinds of findings returned, including which loaded tables fail if a source is unreachable and which queries are orphaned, but it does not state that the tool is read-only, whether it has side effects, or what permissions 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The content is a single semicolon-separated list of output attributes rather than a front-loaded statement of purpose. It is not bloated, but the structure makes the actual action harder to extract than the feature list.

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

Completeness2/5

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

An output schema exists, so the description does not need to enumerate return values, yet nearly all of its text is spent on output details. It leaves critical gaps around the required instance parameter, when to invoke the tool, and how it differs from sibling diagnostics tools.

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?

The single required parameter, instance, has 0% schema description coverage, and the description never mentions it. The agent receives no explanation of what instance should contain or how it affects the analysis.

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

Purpose3/5

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

The description identifies the resource — the query dependency graph — and enumerates what it can reveal, such as chain depth and circular references. However, it opens with a noun phrase rather than a specific verb and does not distinguish this tool from sibling diagnostics tools such as find_query_diagnostics or diagnose_power_query.

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?

It states no conditions for when to use this tool versus alternatives, no prerequisites, and no exclusions. The list of graph facts implies refresh-dependency auditing, but the agent must infer that context from the name alone.

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