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clikader

bitbucket-python-mcp

by clikader

get_file_content

Retrieve the raw content of a file from a BitBucket repository. Useful for reviewing code, configuration files, or documentation.

Instructions

Get the raw content of a specific file from a BitBucket repository.

Use this tool when you need to read the full content of a specific file. This is useful for reviewing code, configuration files, or documentation.

Args: file_path: Path to the file in the repository. repository: Repository slug. If not provided, uses current repository context. workspace: Workspace slug. If not provided, uses the default workspace. ref: Branch, tag, or commit hash (default: HEAD).

Returns: The raw file content as a string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNo
file_pathYes
workspaceNo
repositoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states it returns raw content as a string and mentions defaults for ref, workspace, repository, but does not disclose potential size limits, permissions, or error conditions. Adequate but lacks depth.

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: a one-line summary, a short use-case paragraph, a clear Args list, and a Return statement. Every sentence adds value, no redundancy. Well-structured.

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 4 parameters (1 required) and an output schema, the description covers the function well. It explains defaults, return type, and use cases. Minor gaps: no mention of error handling or file size limits. Mostly complete.

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?

Schema description coverage is 0%, so the description must compensate. It explains each parameter: file_path, repository, workspace, ref, with defaults. This adds meaningful context beyond the schema, making parameter usage clear.

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 it gets the raw content of a specific file from a BitBucket repository. It uses a specific verb ('Get') and resource ('file content'), differentiating it from siblings like get_repository_contents (list files) or search_code.

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 explicitly says 'Use this tool when you need to read the full content of a specific file' and gives examples (reviewing code, config files, docs). It does not specify when not to use or alternatives, but provides clear context for when it is appropriate.

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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