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hasanozcan

Azure DevOps MCP Server

by hasanozcan

Get pull request changed files

get_pull_request_changed_files

Return changed files and line statistics for a pull request iteration to review PR changes in Azure DevOps.

Instructions

Return changed files and locally computed line statistics for a pull request iteration.

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits on its own. It mentions 'locally computed line statistics,' which hints at the output nature, but it does not disclose that this is a read-only operation, any permission requirements, or the effect of optional parameters like maxFiles or iterationId. The description lacks sufficient behavioral detail for a tool with no annotation support.

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, direct sentence that conveys the core action and scope without any unnecessary words. It is appropriately front-loaded with the verb and resource, making it easy to scan and understand.

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?

For a tool with five parameters and no output schema, the description is too minimal. It does not explain the structure of the return value (e.g., file paths, line additions/deletions), the meaning of 'locally computed line statistics,' or the defaults for optional parameters. An agent would need to infer these details from the tool name and schema, leaving room for misinterpretation.

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 schema already provides descriptions for project, repositoryId, and pullRequestId, but not for maxFiles or iterationId. The description adds no parameter-specific meaning, such as clarifying that iterationId defaults to the latest iteration or that maxFiles caps the number of files returned. With schema coverage at 60%, the description does not compensate for the missing parameter documentation.

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 action ('Return') and a specific resource ('changed files and locally computed line statistics') for a pull request iteration. It distinguishes from sibling tools like get_pull_request_diff_stats and get_pull_request_diff by emphasizing 'locally computed' and 'iteration', making the tool's scope unambiguous.

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

Usage Guidelines3/5

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

The description implies usage from its purpose but provides no explicit guidance on when to use this tool versus alternatives such as get_pull_request_diff_stats or get_pull_request_file_diff. It does not state conditions, exclusions, or when to prefer one over another, leaving an agent to infer based on the tool name and context.

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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