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shutdown_runtime

Disconnect and release the active Colab runtime after completing long-running work like training. Save files first to prevent data loss.

Instructions

Disconnects and releases/unassigns the active Colab CPU/GPU runtime instance. Call this as the final cleanup step after training or long runtime work is complete or cancelled. Download needed weights, logs, and artifacts first because /content files can be lost after release. This does not uninstall the MCP server and does not close the browser tab.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional cleanup reason printed before releasing the Colab runtime, for example 'training finished' or 'training cancelled'.
Behavior4/5

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

With no annotations, description carries full burden. Discloses that /content files may be lost after release, and clarifies what the tool does not do (uninstall MCP server or close browser tab). Missing potential side effects like authentication requirements, but adequate for simplicity.

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?

Description is concise with three sentences covering purpose, usage timing, side effect, and exclusions. No wasted words, though could be slightly more structured (e.g., bullet points for non-actions).

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 has one optional parameter and no output schema, the description adequately covers purpose, when to use, side effect, and exclusions. It is complete for the tool's simplicity.

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 coverage is 100% with a single optional 'reason' parameter. Description adds examples ('training finished', 'training cancelled') and clarifies it is printed before release, adding context beyond the schema description.

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 disconnects and releases the active Colab runtime instance. The verb 'Disconnects and releases/unassigns' is specific, and the resource 'active Colab CPU/GPU runtime instance' is unambiguous. This distinguishes it from siblings like restart_runtime or connect_runtime.

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 'Call this as the final cleanup step after training or long runtime work is complete or cancelled.' Provides clear when-to-use context and advice to download artifacts first. Does not explicitly mention alternatives like restart_runtime, but the context is sufficient.

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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