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List GPU templates

list_templates
Read-onlyIdempotent

Browse published AmpleRun templates to compare pinned container images, IDs, engines, minimum VRAM, and GPU counts before choosing a rental runtime.

Instructions

List published AmpleRun templates: pinned container images a rental runs, such as an inference server with fixed model weights or a PyTorch or Jupyter runtime. Returns each template's id, slug (template_id), name, kind, engine, minimum VRAM in bytes and minimum GPU count, plus next_cursor. Read-only; no API key needed. search_offers finds machines for a template.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNomodel: an inference server with pinned weights; classical: a general runtime; custom: other images.
limitNoPage size, 1 to 100.
cursorNonext_cursor from the previous page.
gpu_vram_gibNoOnly templates that fit on a GPU with this much VRAM, in GiB (e.g. 24).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered; the description adds the meaningful auth fact that no API key is needed. It also enumerates returned fields and pagination (next_cursor), giving behavioral context beyond annotations, though no rate limits or ordering guarantees.

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?

Three tight sentences, front-loaded with the operation and object, then returns, then the safety/auth note and sibling pointer. Slightly dense but every clause carries information; nothing is 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?

With no output schema, the description compensates by listing the returned fields and the pagination cursor, and it covers auth and read-only nature for a 4-param list tool. An agent has everything needed to call and interpret it.

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 100% and each parameter (kind, limit, cursor, gpu_vram_gib) is documented in the schema itself with enums and units. The description's enumeration (id, slug, kind, engine, VRAM, GPU count) describes return values rather than adding parameter meaning, so baseline 3 applies.

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?

States a specific verb+resource (List published AmpleRun templates) and immediately defines what a template is, so the agent understands the domain object, not just the operation. It also contrasts with the sibling search_offers, making the distinction clear without opening schemas.

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?

Gives context ('no API key needed') and routes the agent to search_offers for finding machines, which is a useful alternative pointer. However, it does not state explicit when-not conditions or prerequisites (e.g. filtering behavior, whether unauthenticated listings are scoped).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.