list_computersList computers of this account, their Blender and online state, and the computer selected for this chat.
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_computers"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, closed-world semantics, so the safety profile is covered. The description adds real value by disclosing the payload contents (Blender/online state and the currently selected computer), which annotations cannot convey. It stops short of mentioning ordering, caching, or whether the list can be empty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the core action and then the returned facets. Zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, so the description carries the return-value burden and does so by naming the three things the caller gets back. For a parameterless read tool with rich annotations, that is close to fully sufficient; only edge details (empty list, ordering, staleness) are absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Zero parameters, so the baseline is 4. There is no parameter meaning to add, and the description correctly avoids inventing any.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (List) and resource (computers of this account) and enumerates the returned facets: Blender state, online state, and the chat-selected computer. It does not explicitly contrast with the sibling select_computer, so the differentiation is inferential rather than stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not guidance. The sibling select_computer is the natural alternative for changing the selected machine, but the description never names it or says 'use X instead'. The task is simple enough that implied usage is near-obvious, but the definition leaves it unstated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.