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Glama

get_attribute_meta_on_set_class

Read-onlyIdempotent

Retrieve the on-disk FAttributeMetaData DataTable defaults an AttributeSet class initializes from, including row struct, row count, and serialized rows—not live actor values.

Instructions

Read back the FAttributeMetaData DataTable an AttributeSet class is initialized from (read-side of set_attribute_meta_on_set_class): row struct name, row count, and the serialized rows. This reports the AUTHORED defaults on disk, not the live values of any actor -- for those use get_attribute_value / get_attributes.

Returns: { attribute_set_class, data_table_path, row_struct, row_count, rows }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_table_pathNoOptional override; default is /Game/UEAgent/AttributeMeta/<ClassName>_Meta
attribute_set_class_pathYesFull UAttributeSet class path

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile needs no restating. The description earns its keep by disclosing the key behavioral distinction: authored on-disk defaults versus live actor values, plus the shape of what is returned. It stops short of details like pagination or behavior for missing tables, but is solidly above the annotation baseline.

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?

Two tight sentences front-load the resource and its non-live-values caveat, followed by a compact Returns block. No filler, and the most decision-relevant information comes first.

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, but the description supplies the return shape (attribute_set_class, data_table_path, row_struct, row_count, rows) and the semantic distinction between authored and live values. For a read-only two-parameter lookup, nothing an agent needs 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 description coverage is 100%, and both parameters (including the optional data_table_path default) are documented in the schema itself, so the baseline is 3. The description's Returns block adds output context but does not extend parameter meaning beyond what the schema states.

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 states a specific read verb and a precisely named resource ('the FAttributeMetaData DataTable an AttributeSet class is initialized from') and frames itself as the read-side counterpart of set_attribute_meta_on_set_class. An agent can distinguish it from get_attribute_value / get_attributes without opening any schema.

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?

It explicitly states when-not-to-use ('this reports the AUTHORED defaults on disk, not the live values of any actor') and names the alternatives that cover that case (get_attribute_value / get_attributes). The write-side sibling is called out by name, so routing is unambiguous.

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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