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List Node Graph Asset Types

list_graph_node_assets
Read-only

List registered node-template asset IDs for a node space to get valid $type values for apply_graph_description. Filters scene-node templates to those addable in that space.

Instructions

Enumerate registered node-template asset ids for a node space — the ids you pass to apply_graph_description as $type. For the scene-nodes (neutron) space, results are filtered to the templates actually addable there (e.g. 'net.maxon.node.invert', 'net.maxon.node.access.composecolor64'); note these differ from the net.maxon.corenode:* ids that list_graph_nodes reports for existing nodes. supported:false comes back when the C4D build lacks the maxon framework.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_spaceNoAlias 'standard' | 'redshift' | 'scenenodes' (a.k.a. 'neutron') or a fully-qualified maxon.Id. Default 'standard'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.3.1

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safe-read nature is known. The description adds meaningful behavioral details beyond that: the filtering behavior specific to the scene-nodes space, and the fact that `supported:false` is returned when the build lacks the maxon framework. These are operational quirks an agent would otherwise not know, so the description adds real value.

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 sentences with zero fluff. The first sentence states the core purpose and ties it to a specific use case. The second adds a domain-specific nuance about filtering, and the third covers an edge-case response. Every sentence earns its place, and the most critical info (purpose and usage) is front-loaded.

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 read-only listing tool with one parameter and no output schema, the description is essentially complete: it explains what the tool returns, how to use the results, a special case (scene-nodes filtering), and a failure indicator (`supported:false`). The only thing missing is a precise description of the output format, but that may be implied by the tool's nature and the absence of an output schema. An agent has enough to call this tool correctly.

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?

The single parameter `node_space` is fully described in the schema (100% coverage) with its alias options, default value, and acceptance of fully-qualified maxon.Id. The description does not add new semantic details about the parameter itself—it only explains how the parameter value affects filtering, which is more of a behavioral note. Since the schema already covers parameter meaning, a baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states the verb 'enumerate' and the resource 'node-template asset ids for a node space', and immediately ties it to the `$type` parameter in `apply_graph_description`. It explicitly distinguishes these ids from the `net.maxon.corenode:*` ids reported by `list_graph_nodes`, making it easy for an agent to tell the two tools apart without inspecting schemas.

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?

The description provides concrete usage context by specifying that the returned ids are what you pass to `apply_graph_description` as `$type`. It also notes that results for the scene-nodes space are filtered to addable templates, giving the agent a condition to watch for. It doesn't explicitly say 'use this when you need X and not when you need Y', but the sibling differentiation and use-case tie make the intended usage clear enough.

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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