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clikader

bitbucket-python-mcp

by clikader

list_pull_requests

List pull requests in a BitBucket repository, filtering by state, workspace, or repository to track open requests or review history.

Instructions

List pull requests in a BitBucket repository.

Use this tool to see pull requests in a repository. By default, shows only open pull requests.

Args: repository: Repository slug. If not provided, uses current repository context. workspace: Workspace slug. If not provided, uses the default workspace. state: Filter by state - 'OPEN', 'MERGED', 'DECLINED', or 'SUPERSEDED'. Default is 'OPEN'. limit: Maximum number of pull requests to return. Default 10.

Returns: JSON list of pull requests with their titles, authors, and status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
stateNoOPEN
workspaceNo
repositoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses default state filter (OPEN), default limit (10), and fallback context for repository/workspace. Lacks mention of error cases, pagination, or ordering, but for a simple list tool this is adequate. No annotations present, so description carries the full burden.

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 brief and front-loaded, with a clear opening sentence then structured Args section. Every sentence adds value, no fluff.

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?

Given the output schema exists (so return values need not be detailed), the description covers parameters, defaults, and filter options well. Could mention maximum limit or additional behavior like ordering, but overall sufficient for a list operation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by explaining each parameter's purpose (repository slug, workspace slug, state filter with enumerated values, limit). Adds meaning beyond the schema's types and defaults, including contextual defaults.

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 'List pull requests in a BitBucket repository' with a specific verb and resource. It distinguishes from sibling tools like get_pull_request (single PR) and create_pull_request by implying a list operation, and adds default behavior context.

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?

Provides basic guidance ('Use this tool to see pull requests in a repository') and defaults, but does not explicitly differentiate from alternatives like get_pull_request for a single PR or mention when not to use it. More explicit comparisons would improve clarity.

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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