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Acendas

Bitbucket MCP Server

by Acendas

create_branch

Create a new branch in a Bitbucket repository by specifying source commit, branch, or tag for version control workflows.

Instructions

Create a new branch in a repository.

Args: repo_slug: Repository slug (name) name: Name for the new branch target: Commit hash, branch name, or tag to branch from workspace: Bitbucket workspace (optional if configured)

Returns: Created branch details or error message

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repo_slugYes
nameYes
targetYes
workspaceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool creates a branch and returns details or an error, but lacks critical information such as required permissions, whether it's idempotent, potential side effects (e.g., branch naming conflicts), or rate limits. This is inadequate for a mutation tool with zero annotation coverage.

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 well-structured with clear sections (purpose, args, returns) and uses bullet points for readability. It's front-loaded with the main purpose, and each sentence adds value without redundancy. A slight improvement could be merging the args list into a more concise narrative, but overall it's efficient.

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 complexity (a mutation with 4 parameters), no annotations, and an output schema present (which handles return values), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral details like error conditions or usage context. This is the minimum viable for such a tool, with clear room for enhancement.

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 lists all four parameters with brief explanations (e.g., 'target' as 'Commit hash, branch name, or tag to branch from'), which adds meaningful context beyond the schema's type definitions. However, it doesn't cover constraints like format requirements or examples, leaving some gaps.

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 ('Create a new branch') and resource ('in a repository'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'create_tag' or 'fork_repository', which also create things in repositories, so it misses the top score.

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. For example, it doesn't mention when to use 'create_branch' compared to 'create_pull_request' or 'fork_repository', nor does it specify prerequisites like repository access or authentication needs. This leaves the agent with minimal context for tool selection.

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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