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emt_environments

Read-onlyIdempotent

Verified environments (PyTorch, JAX, vLLM, TensorRT-LLM, ComfyUI, Unsloth) with their CUDA version and ports. Checked against the node before renting; they start an SSH server with the order's key.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "emt_environments"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), and the description adds genuine context beyond them: environments are verified against the node, and images boot an SSH server using the order's key. That tells the agent what a returned environment actually guarantees. It leaves some ambiguity about how verification happens given the tool takes no node parameter, which is why it is not a 5.

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?

Two tight sentences, front-loaded with the resource and its concrete examples before the behavioral note about verification and SSH. Every clause carries information; only the slightly compressed 'they start an SSH server with the order's key' phrasing could be clearer.

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?

With no input schema, no output schema, and rich annotations, the description carries only the burden of describing the result shape — and it does that by naming CUDA version and ports as returned fields. A short note on ordering or filtering of the list would make it fully complete.

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 takes zero parameters, so there is nothing for the description to disambiguate and the baseline applies. The description wisely spends its words on what the tool returns instead of inventing parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource concretely and enumerates example environments (PyTorch, JAX, vLLM, TensorRT-LLM, ComfyUI, Unsloth) plus the attributes returned (CUDA version, ports), so an agent knows exactly what this yields. The verb is implicit (list/retrieve) and it never distinguishes itself from sibling catalog-like tools such as emt_catalog or emt_templates, which keeps it from a 5.

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

Usage Guidelines3/5

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

The phrase 'Checked against the node before renting' implies the usage context — consult this before calling emt_rent — but the guidance is indirect rather than an explicit 'use this when X, use emt_catalog when Y'. No alternatives or exclusions are named despite several similarly-shaped siblings.

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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