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Acendas

Bitbucket MCP Server

by Acendas

fork_repository

Create a copy of a Bitbucket repository to modify independently, enabling experimentation or contribution without affecting the original source.

Instructions

Fork a repository.

Args: repo_slug: Repository slug (name) to fork new_name: Name for the forked repository (optional, defaults to original name) workspace: Bitbucket workspace (optional if configured)

Returns: Forked repository details or error message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_slugYes
new_nameNo
workspaceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Fork a repository') but doesn't describe what forking entails (creates a copy, maintains link to original), permission requirements, rate limits, or what happens if the repository already exists. The mention of 'Returns: Forked repository details or error message' adds minimal behavioral context.

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 appropriately sized and front-loaded with the core purpose. The Args/Returns structure is clear, though slightly redundant with schema. Every sentence earns its place, but the 'Returns' line could be more informative given the output schema exists.

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 3 parameters with 0% schema coverage and no annotations, the description provides basic parameter semantics but lacks behavioral context for a mutation operation. The existence of an output schema means return values don't need explanation, but the description should do more to explain the fork operation's implications, permissions, and error conditions.

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?

Schema description coverage is 0%, so the description must compensate. It provides basic semantic meaning for all three parameters: 'repo_slug' as the repository to fork, 'new_name' as optional name for the fork, and 'workspace' as optional Bitbucket workspace. However, it doesn't explain format requirements (e.g., slug conventions), default behaviors beyond 'new_name', or when workspace is required versus optional.

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 action ('Fork a repository') with a specific verb and resource. It distinguishes this from sibling tools like 'create_repository' or 'list_repository_forks' by focusing on the fork operation. However, it doesn't explicitly contrast with these siblings in the description text itself.

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. It doesn't mention prerequisites (like authentication or permissions), when forking is appropriate versus creating a new repository, or how it differs from 'list_repository_forks'. The agent must infer usage context from the tool name alone.

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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