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dam2452

vastai-mcp

by dam2452

search_templates

Search user and public templates on Vast.ai using filters like tags to find matching machine images.

Instructions

Search user and public templates (GET /template/).

The endpoint always requires a select_filters body (pass {} for "all"). This tool defaults to {} when called without arguments.

Examples: search_templates() search_templates(select_filters={"tag": {"eq": "pytorch"}})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
select_filtersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It explicitly discloses the endpoint method, the required body constraint, and the default behavior ('defaults to {}'). It does not discuss auth or rate limits, but the 'search' verb implies read-only, and the examples clarify invocation behavior.

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 concise and front-loaded with the purpose. Each sentence adds value: the endpoint, the body requirement, the default behavior, and two examples. There is no wasted text, and the examples make the usage immediately understandable.

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?

Given the tool's simplicity (one optional parameter, output schema present, no annotations), the description is complete enough. It covers the parameter semantics, default behavior, and provides examples. Return values are presumably covered by the output schema, so no additional return description is needed.

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 coverage is 0%, so the description fully compensates by explaining the `select_filters` parameter: it shows the format for 'all' (`{}`) and provides a concrete example with a tag filter (`{"tag": {"eq": "pytorch"}}`). This adds meaning far beyond the bare schema definition of object/null.

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: 'Search user and public templates', with the specific endpoint '(GET /template/)'. This uses a specific verb and resource, and the resource 'templates' distinguishes it from siblings like search_offers and search_benchmarks.

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 usage context: it explains that the endpoint requires a `select_filters` body, shows how to pass `{}` for 'all', and includes two practical examples. It does not explicitly mention alternative tools, but the distinct resource makes alternatives unnecessary; context is clear enough.

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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