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hasanozcan

Azure DevOps MCP Server

by hasanozcan

Get pull request diff

get_pull_request_diff

Retrieve a unified diff for an Azure Repos pull request to review code changes, using filters like repository, pull request ID, iteration, and file or line limits.

Instructions

Build and return a unified diff for an Azure Repos pull request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNoProject name or ID. Omit to use AZURE_DEVOPS_DEFAULT_PROJECT.
maxFilesNo
maxLinesNo
startLineNo
iterationIdNo
contextLinesNo
repositoryIdYesRepository name or ID.
pullRequestIdYesPull request numeric ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the core action and does not mention important behaviors such as truncation based on maxFiles/maxLines, handling of iterationId, or any limits on the diff size. The description omits potential side effects or output formatting details, leaving agents guessing.

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?

The description is a single, front-loaded sentence with no wasted words. It is concise and follows a clear verb-object structure. However, given the tool's complexity (8 parameters, no output schema), it is arguably too sparse, but the dimension rewards conciseness and front-loading, which are achieved.

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?

The description is inadequate for the tool's complexity. With no output schema, no annotations, and multiple undocumented parameters, the agent lacks essential context about return format, limits, or how to use optional parameters. The description does not mention pagination, truncation, or what constitutes a 'unified diff', making it incomplete for correct invocation.

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 only 38%, and the tool description does not compensate. Parameters like maxFiles, maxLines, startLine, iterationId, and contextLines have no descriptions in the schema or the description, leaving their semantics ambiguous. For example, iterationId and contextLines are not self-explanatory, and the description provides no clarification.

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?

The description clearly states a specific verb ('Build and return') and a specific resource ('unified diff for an Azure Repos pull request'). It distinguishes itself from sibling tools like get_pull_request_diff_stats and get_pull_request_file_diff, which have different outputs, so an agent can identify its purpose without confusion.

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. There are many related PR diff tools (diff_stats, file_diff, changed_files), but the description does not mention any of them or suggest conditions for choosing this one. An agent would have to infer usage 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.

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