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ennuiii

Azure DevOps MCP Server with PAT Authentication

by ennuiii

repo_list_pull_requests_by_repo

Retrieve a filtered list of pull requests from a specific Azure DevOps repository. Filter by status, creator, reviewer, or paginate results using top and skip parameters.

Instructions

Retrieve a list of pull requests for a given repository.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
created_by_meNoFilter pull requests created by the current user.
i_am_reviewerNoFilter pull requests where the current user is a reviewer.
repositoryIdYesThe ID of the repository where the pull requests are located.
skipNoThe number of pull requests to skip.
statusNoFilter pull requests by status. Defaults to 'Active'.Active
topNoThe maximum number of pull requests to return.
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 states the action ('Retrieve a list') but doesn't mention whether this is a read-only operation, if it requires authentication, what the return format looks like (e.g., paginated list), or any rate limits. For a tool with 6 parameters and no annotations, this leaves significant behavioral gaps.

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, straightforward sentence that efficiently conveys the core action. It's front-loaded with the main purpose and wastes no words, though it could be slightly more informative without losing conciseness.

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

Completeness3/5

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

Given the tool's moderate complexity (6 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on usage context, behavioral traits, or output expectations. With no output schema, the description doesn't compensate by explaining return values, leaving room for improvement.

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, with each parameter clearly documented (e.g., 'repositoryId' as the repository ID, 'status' with enum values). The description adds no additional parameter semantics beyond what the schema provides, but since schema coverage is high, 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 verb ('Retrieve') and resource ('list of pull requests for a given repository'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'repo_list_pull_requests_by_project' or 'repo_list_pull_requests_by_commits', but the 'by_repo' in the name implies repository-specific filtering.

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 like 'repo_list_pull_requests_by_project' or 'repo_get_pull_request_by_id'. It doesn't mention prerequisites, such as needing repository access, or suggest scenarios where this tool is preferred over others.

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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