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azure-devops MCP Server

azure-devops MCP Server

by mmruesch12
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_pull_request_diff

Retrieve the difference for a specific pull request in Azure DevOps, optionally filtering by file path or iteration for precise changes.

Instructions

Get the diff for a pull request

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": {
      "pullRequestId": "<pullRequestId>"
    },
    "name": "get_pull_request_diff"
  }
}

Input Schema

NameRequiredDescriptionDefault
filePathNoSpecific file path to get diff for (optional)
iterationIdNoSpecific iteration to get diff for (optional)
pullRequestIdYesID of the pull request

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool gets a diff but does not explain what the diff includes (e.g., patch format, line changes), whether it requires authentication, rate limits, or error handling. This is a significant gap for a tool with no annotation coverage.

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?

The description is a single, efficient sentence with zero waste. It is front-loaded and directly states the tool's purpose without unnecessary elaboration, making it highly concise and well-structured.

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?

Given the complexity of a diff tool with no annotations and no output schema, the description is incomplete. It lacks details on the diff format, error cases, or behavioral traits, which are crucial for an agent to use the tool effectively. The schema covers parameters well, but overall context is insufficient.

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 input schema has 100% description coverage, clearly documenting all three parameters (pullRequestId, filePath, iterationId) with their types and optionality. The description adds no additional parameter semantics beyond what the schema provides, so the baseline score of 3 is appropriate.

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 clearly states the action ('Get') and resource ('diff for a pull request'), making the purpose understandable. However, it does not distinguish this tool from potential siblings like 'get_pull_request' (which might return metadata rather than diff content), leaving room for ambiguity in sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_pull_request' (likely for metadata) and 'list_pull_requests' (for listing), there is no indication of context, prerequisites, or exclusions, leaving usage unclear.

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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