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tom275275

Google Workspace MCP Server

by tom275275

get_script_content

Retrieve file contents from a Google Apps Script project by providing the script ID and file name. Returns the source code as a string for review or processing.

Instructions

Retrieves content of a specific file within a project.

Args: service: Injected Google API service client user_google_email: User's email address script_id: The script project ID file_name: Name of the file to retrieve

Returns: str: File content as string

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_nameYes
script_idYes
user_google_emailYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.14.3

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry behavioral context. 'Retrieves' and 'Returns: str: File content as string' make the read-only nature and output clear. It also notes that the service client is injected, which is useful. However, it doesn't disclose error behavior, permissions, or rate limits. For a simple read tool this is adequate but not rich.

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 structured with a clear opening sentence, an Args block, and a Returns block. It is appropriately sized for a tool with 3 parameters, with no redundant prose. The main purpose is front-loaded, making it easy to scan.

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?

For a simple file-content getter, the description covers the essential operational context: the injected service, required identifiers, and return type. The output schema also documents the return value. It doesn't address error cases, but these are not critical for straightforward retrieval. Overall, an agent can invoke this tool correctly with the given information.

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. The Args section gives a one-line description for each parameter, but these mostly restate the parameter names ('User's email address', 'The script project ID', 'Name of the file to retrieve'). It does clarify that 'service' is injected and not part of the schema, which adds value. Overall, it provides only minimal additional meaning beyond the names and types.

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?

States a specific verb ('Retrieves') and resource ('content of a specific file within a project'). This clearly differentiates it from sibling tools like get_script_project (project metadata) and get_drive_file_content (Drive files). The description is precise and immediately actionable.

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?

Provides clear context: use when you need the source content of a file inside an Apps Script project. It does not explicitly mention alternatives or exclusion cases, but the specificity of the purpose makes the appropriate use case obvious among the large sibling list.

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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