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clikader

bitbucket-python-mcp

by clikader

get_default_reviewers

Retrieve default reviewers configured for a Bitbucket repository to see automatically added reviewers for pull requests.

Instructions

Get default reviewers configured for a repository.

Use this tool to see which users are automatically added as reviewers when creating pull requests. These reviewers will be included unless explicitly excluded.

Args: repository: Repository slug. If not provided, uses current repository context. workspace: Workspace slug. If not provided, uses the default workspace.

Returns: JSON list of default reviewers with their details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceNo
repositoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description discloses key behavioral traits: it indicates the tool reads configuration (implied by 'get'), explains that reviewers are automatically added unless excluded, and notes default context usage for parameters. It does not mention permissions or error handling, but the behavior is adequately conveyed.

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 concise, with a clear opening statement, a usage hint, and a structured Args section. Every sentence serves a purpose, and the information is front-loaded.

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 simple read operation and the presence of an output schema, the description covers the essential aspects: what the tool does, when to use it, parameter details, and return format. It lacks error scenarios or advanced context, but it is complete enough for typical use.

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

Parameters4/5

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

The input schema has 0% description coverage, so the description compensates by explaining the purpose of each parameter ('Repository slug', 'Workspace slug') and their default behavior ('If not provided, uses current...context'). This adds significant value beyond the schema's basic type information.

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 retrieves default reviewers for a repository, with a specific verb and resource. It distinguishes itself from sibling tools by focusing solely on default reviewers.

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

Usage Guidelines4/5

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

The description explains when to use the tool ('to see which users are automatically added as reviewers when creating pull requests') and provides context about reviewer inclusion. However, it does not explicitly mention when not to use it or list alternatives.

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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