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dam2452

vastai-mcp

by dam2452

list_instances

List all GPU instances in your Vast.ai account, with optional label filtering, to view and manage your rentals.

Instructions

List the authenticated user's instances (GET /instances/).

Examples: list_instances() list_instances(label="vllm-inference")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the full burden. It adds the scoping fact that only the authenticated user's instances are listed, which is useful. However, it does not disclose whether the operation is read-only, any authorization requirements, or behavior like pagination or filtering semantics beyond the example. This is adequate but minimal.

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, front-loaded with the core purpose, and includes two clear usage examples. Every element earns its place with no fluff.

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 simple nature of the tool (one optional parameter, output schema exists), the description covers the core operation and examples adequately. It lacks caveats about pagination or rate limits, but these are less critical for a simple list operation with an output schema.

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 examples show how to pass a label, hinting that it filters instances, but the description never explicitly explains the label parameter's meaning. This marginal addition is slightly better than nothing but not a full semantic explanation.

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 lists the authenticated user's instances and includes the API endpoint (GET /instances/). This is a specific verb+resource combination that distinguishes it from siblings like get_instance or create_instance.

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?

The description provides clear context (lists the user's own instances) but does not explicitly state when to use this tool versus alternatives like get_instance or search_offers. It gives examples of how to call it 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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