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by io.github.aeonmindai
OverviewDiscussionsAdmin

List instances

list_instances
Read-onlyIdempotent

List all GPU instances in your workspace. Returns name, status, GPU type, kind (deployment_type: vm, baremetal or container), who runs it (host: "Datacenter" or "Community host"; A community host is run by an independent host, not a datacenter: the host operates the hardware and can access the machine, and it is not available on reserved terms.), IP, and cost.

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": "list_instances"
  }
}

Input Schema

NameRequiredDescriptionDefault
searchNoFilter instances by name
workspaceNoWorkspace ID (optional: defaults to the authenticated workspace)
environmentNoEnvironment name (optional: defaults to the environment this session acts in)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • removedInput schema / properties / env
      Removed value: -{
-  "description": "Environment name (optional — defaults to main)",
-  "type": "string"
-}
    • addedInput schema / properties / environment
      Added value: +{
+  "description": "Environment name (optional: defaults to the environment this session acts in)",
+  "type": "string"
+}
    • changedInput schema / properties / workspace / description
      Previous value: -"Workspace ID (optional — defaults to authenticated workspace)"New value: +"Workspace ID (optional: defaults to the authenticated workspace)"
  2. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered in structured data. The description's contribution is the returned field set (name, status, GPU type, kind, host, IP, cost) plus the semantic gloss on "Community host" — genuinely useful since no output schema exists, but it says nothing about pagination, result limits, or ordering.

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 sentences, front-loaded with the action and followed by the return payload, which is the right ordering for a list tool. The nested clarification of community hosts is wordy and only marginally relevant to selecting or invoking the tool, keeping it from a top score.

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 output schema, the enumeration of returned fields is exactly what an agent needs to decide whether this call answers its question, and the three optional parameters are fully covered by the schema. The absence of any note on result volume or ordering is a minor gap for a tool whose name implies an unbounded list.

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%, so search, workspace, and environment are already documented in the input schema, which sets the baseline at 3. The description only implies the workspace-scoping default ("in your workspace") and adds no detail on substring-matching behavior for search or the session-environment default.

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 opens with a specific verb and resource: "List all GPU instances in your workspace," which is unambiguous. It does not, however, distinguish itself from siblings like get_instance (single-instance retrieval) or list_gpu_types, leaving the agent to infer the boundary from names alone.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance, and no mention of alternatives such as get_instance for a single machine or list_clusters for cluster membership. The workspace scoping phrase hints at context, but selection between this and sibling list tools is left entirely to inference.

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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