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colab_drive_upload

Upload a local file to a specified Google Drive folder to stage data for Colab GPU runtimes. Use with colab_execute's drive_fetch parameter.

Instructions

Upload a local file to Google Drive.

Use this to stage input data before running colab_execute with the drive_fetch parameter. The file is uploaded to the specified folder under MyDrive.

After upload:

  • Pass the drive path in colab_execute's drive_fetch parameter to make the file available on the Colab runtime.

  • Example: colab_execute(code="...", drive_fetch='{"colab_data/train.csv": "/content/train.csv"}')

Common issues:

  • First use requires Google Drive OAuth authorization (browser popup).

  • Nested folders (e.g. 'data/train') are created automatically.

Args: local_path: Path to the local file to upload. drive_folder: Target folder path on Google Drive (relative to MyDrive). Nested paths like 'data/train' are supported. Folders are created automatically if they don't exist. Default: "colab_data".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
local_pathYes
drive_folderNocolab_data

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Discloses OAuth authorization requirement and automatic folder creation. Annotations already indicate non-read-only and non-destructive nature. Missing details about overwrite behavior and file size limits.

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?

Well-structured with separate sections for usage, post-upload steps, common issues, and Args. Concise but not overly terse; each sentence adds useful information.

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?

Covers prerequisites (OAuth), integration with colab_execute, and common issues. Output schema exists but description doesn't mention return value; still fairly complete for the tool's purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has no parameter descriptions (0% coverage). Description explains both parameters thoroughly: local_path is path to local file, drive_folder includes default value, nested folder support, and auto-creation. Adds significant value beyond the schema.

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?

Clear verb 'Upload', specific resource 'local file to Google Drive', and distinguishes from sibling tools by mentioning its role in staging data for colab_execute.

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?

Explicitly states when to use: before colab_execute with drive_fetch parameter. Provides usage example and mentions OAuth prerequisite, but lacks explicit when-not-to-use guidance.

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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