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Tiberriver256

Azure DevOps MCP Server

get_pull_request_checks

Summarize latest status checks and policy evaluations for a pull request, surfacing pipeline and run identifiers to identify blocking validations and enable deeper failure inspection.

Instructions

Summarize the latest status checks and policy evaluations for a pull request.

  • Surfaces pipeline and run identifiers so you can jump straight to the blocking validation.

  • Pair with pipeline tools (e.g., get_pipeline_run, pipeline_timeline) to inspect failures in depth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdNoThe ID or name of the project (Default: MyProject)
organizationIdNoThe ID or name of the organization (Default: mycompany)
repositoryIdYesThe ID or name of the repository
pullRequestIdYesThe ID of the pull request
Behavior3/5

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

The description explains the tool summarizes and surfaces identifiers but does not explicitly state that it is read-only or non-destructive. With no annotations, the description carries the full burden, and while the behavior is implied, it lacks explicit safety disclosure.

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 two sentences and a bullet point, front-loaded with purpose, and every sentence adds value without repetition or filler.

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

Completeness4/5

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

The description explains the output is a summary of status checks and surfaces pipeline/run identifiers, which is adequate for a read tool. However, without an output schema, more detail on the returned fields would improve completeness.

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?

Input schema has 100% parameter description coverage, so baseline is 3. The description does not add parameter-specific meaning beyond what the schema already provides (e.g., what projectId or pullRequestId mean).

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 the tool 'summarize[s] the latest status checks and policy evaluations for a pull request,' using a specific verb and resource. This differentiates it from siblings like get_pull_request (gets the PR itself) and get_pull_request_changes.

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

Usage Guidelines5/5

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

The description explicitly guides pairing with pipeline tools (e.g., get_pipeline_run, pipeline_timeline) to inspect failures, indicating when to use this tool as an overview and when to use alternatives for deeper inspection.

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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