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delete_material_expression

Destructive

Remove one named node from a material graph, safely clearing nodes one at a time to avoid the duplicate parameters that bulk deletion leaves behind.

Instructions

Delete ONE node from a material graph by name. Deliberately one at a time, and that is the safe way to empty a graph: the engine's bulk delete_all_material_expressions can leave half the nodes behind with no error, and a rebuild on top then produces duplicate parameter names that no parameter listing reveals (duplicates collapse by name). Loop this instead, re-reading get_material_expressions until the count reaches 0. The underlying engine call also returns false while having done the work, so count the nodes rather than trusting the flag.

Returns: { material_path: string, expression_name: string, success: bool }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
material_pathYesFull path to the material (e.g., '/Game/Materials/MyMaterial.MyMaterial')
expression_nameYesName of the material expression to delete

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare destructiveHint=true and non-idempotent, but the description adds substantial non-obvious context: the bulk call silently leaves nodes behind, orphaned nodes cause duplicate parameter names that listings hide, and the engine call returns false while still performing the work. This is exactly the sort of behavioral disclosure annotations cannot carry.

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?

Front-loads the core action, then layers the caveats and the loop procedure. Dense but nearly every sentence carries information; the failure-mode explanation is longer than strictly needed but justified by its non-obviousness.

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

Completeness5/5

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

There is no output schema, and the description supplies the return shape ({material_path, expression_name, success}) plus the crucial instruction to verify via node count rather than the success flag. Nothing needed to invoke or verify the call is missing.

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 coverage is 100% and both parameters are documented there, so the schema does the heavy lifting. The description adds only that deletion is by name (implying expression_name uniquely identifies the node); no format or path-instance nuance beyond the schema.

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?

States a specific verb and resource with explicit scope: 'Delete ONE node from a material graph by name.' The emphasis on singularity and the contrast with bulk delete makes the tool's identity unambiguous relative to siblings.

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

Usage Guidelines5/5

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

Explicitly names the alternative (delete_all_material_expressions) and why to avoid it, then gives the recommended procedure: loop this call and re-read get_material_expressions until the count reaches 0. When-to-use and how-to-use are both covered.

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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