Skip to main content
Glama

get_file_tool

Retrieve file content and metadata from a GitLab repository using project ID and file path. Specify an optional branch, tag, or commit SHA to fetch a specific version.

Instructions

Get a file from a GitLab repository.

Returns file metadata and content (base64 encoded).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoBranch, tag, or commit SHA (default: HEAD)HEAD
file_pathYesPath to the file in the repository
project_idYesProject ID or path

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 discloses that content is base64 encoded, which is useful, but does not explicitly note that the operation is read-only (though obvious from 'get') or detail any potential error conditions. The description provides minimal but sufficient behavioral context for a simple read operation.

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 extremely concise—two sentences that immediately state the purpose and a key output detail. There is no filler or repetition, making it easy to parse quickly.

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 tool's simplicity, the description adequately covers its role and output format. The presence of a complete output schema and well-documented parameters means the agent has enough information to invoke it correctly. Minor gaps like specifying that ref defaults to HEAD are already in the schema, so the description need not repeat them.

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?

The schema already provides descriptions for all three parameters (100% coverage), so the baseline is 3. The description does not add any additional parameter-specific nuances beyond what the schema states; it only mentions output encoding, not parameter behavior. Thus, it adds no extra meaning to parameters.

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 fetches a file from a GitLab repository, with a specific verb ('Get') and resource (file). It also distinguishes from siblings like list_repository_tree (which lists contents) and create/update_file (which write). The return content being base64 is an additional clarifying detail.

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?

The description implies the tool is for reading file contents, but it does not explicitly discuss when to use it versus alternatives like list_repository_tree or search tools. There are no explicit when/when-not instructions or named alternatives, so guidance is limited to what can be inferred from the name and purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/crunchtools/mcp-gitlab'

If you have feedback or need assistance with the MCP directory API, please join our Discord server