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Check Sandbox Runtime

check_sandbox_runtime

Verify that the sandbox runtime is active, confirm Docker connectivity, and retrieve isolation defaults. Use this when an experiment creation fails to determine whether the Docker daemon is stopped or the request was rejected.

Instructions

Confirm the sandbox runtime is available and report the active defaults.

USE THIS first if create_experiment fails, to tell a stopped Docker daemon apart from a rejected request. Returns the Docker version the server is talking to and the isolation defaults every experiment starts from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses that the tool returns the Docker version and isolation defaults, and frames the action as a non-mutating check. It could further clarify failure behavior, but for a zero-parameter diagnostic tool this is sufficient.

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 compact and front-loaded: the first sentence states the core purpose, and the second adds a valuable usage cue and return details. Every sentence earns its place with no repetition or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (0 params, output schema present), and the description fully covers when to use it, what it does, and what it returns. Nothing essential is missing for an agent to select and call it correctly.

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?

The tool has zero parameters and an empty input schema, so parameter documentation is not needed. The description correctly focuses on behavior and output rather than parameter details, matching the baseline for parameter-less tools.

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's function: confirm sandbox runtime availability and report active defaults. It names the specific resource (sandbox runtime) and the exact outputs (Docker version, isolation defaults), distinguishing it from experiment-related siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit situational guidance: use this first if create_experiment fails to distinguish a stopped Docker daemon from a rejected request. This directly tells an agent when to invoke it over alternatives.

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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