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query_objects

Read-onlyIdempotent

Retrieve status data for specified Klipper objects by passing object names, or omit names to list all available objects.

Instructions

Escape hatch for arbitrary Klipper status objects. Pass a list of object names (e.g. ['bed_mesh','probe','mcu']); omit to get the full object list instead. Use get_capabilities first to see what exists.

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": "query_objects"
  }
}

Input Schema

NameRequiredDescriptionDefault
objectsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.1

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds the meaningful behavioral detail that omitting the argument returns the full object list rather than erroring, but says nothing about result size, shape or failure modes for unknown object names.

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?

Three short sentences, front-loaded with the core purpose, then the parameter contract, then the prerequisite. No filler or redundant restatement of the tool name.

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?

For a one-optional-parameter read tool with an output schema and full safety annotations, the description covers purpose, argument semantics and the recommended discovery step. Only edge-case behavior for unknown object names is left unaddressed.

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?

Schema coverage is 0% for the single 'objects' parameter, so the description carries the burden and does so: it specifies that a list of names is expected, gives example values, and defines the null/omitted behavior. What is missing is guidance on invalid or unknown names.

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 a specific verb+resource: querying arbitrary Klipper status objects via a list of object names, and gives concrete examples (['bed_mesh','probe','mcu']). The 'escape hatch' framing signals it is the generic fallback relative to dedicated query tools, though it does not name any specific sibling.

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?

It gives a clear prerequisite ('Use get_capabilities first to see what exists') and explains the omit-vs-pass branching. It stops short of explicitly saying when to prefer a dedicated sibling such as query_probe over this generic path.

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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