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get_parameters

Read many Houdini parameter values at once, matched by name or label substring, with filters for node path, node type, patterns, values, and non-default parameters.

Instructions

Read many parameter values at once, matched by name or label substring.

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": "get_parameters"
  }
}

Input Schema

NameRequiredDescriptionDefault
insideNo
patternsNo
node_pathNo
node_typeNo
recursiveNo
value_containsNo
include_defaultsNo
non_default_onlyNo
include_locked_assetsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, yet it only implies a read operation. It does not say whether a node path is needed to scope results, what 'recursive' or 'include_locked_assets' change about behavior, whether the call can be expensive on large scenes, or what the results look like.

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?

A single front-loaded sentence with no filler and no repetition of the tool name. It is efficient, though the terseness is more a symptom of missing content than a virtue at this parameter count.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a nine-parameter query tool with no annotations and no output schema, the definition is far too thin. An agent cannot tell how the filters combine, which filters are mutually exclusive, or how results are shaped, so correct invocation would require guesswork.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across nine parameters, and the description explains almost none of them. 'Matched by name or label substring' loosely gestures at 'patterns', but node_path, node_type, inside, value_contains, recursive, include_defaults, non_default_only, and include_locked_assets are left completely undefined in both schema and prose.

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?

States a specific verb ('Read') plus resource ('parameter values') and scope ('many at once'), and adds the matching rule ('by name or label substring'). That clearly separates it from write-side siblings like set_parameters, though it does not distinguish it from nearby read tools such as get_attrib_values.

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?

Usage is only implied: an agent can infer it should call this when it wants multiple parameter values rather than setting them. There is no explicit when-to-use statement, no mention of prerequisites such as needing a node context, and no routing to alternative readers.

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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