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CarlxsMG

UEAgent

by CarlxsMG
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set_blackboard_value

DestructiveIdempotent

Set a blackboard key value on an editor-world actor, converting string input by key type for runtime AI testing in Unreal Editor. Use it for editor-only state; verify with get_blackboard_value.

Instructions

Write one key of the running blackboard of an editor-world actor, converting the value string by key type. Not read back: set is always true, and an unparsable number or vector is written as 0. Runtime state only, nothing saved; editor world only, never PIE. Verify with get_blackboard_value.

Returns: { actor_name: string, key_name: string, key_type: string, value: string, set: bool }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueNoValue as a string, converted by key type: "42", "0.5", "true" or "1", a name, an enum index, a vector "X=1 Y=2 Z=3", a rotator "P=0 Y=90 R=0", an object or class path. Omitted means empty (0, false, none).
key_nameYesName of the blackboard key to set
actor_nameYesName of the actor whose blackboard to modify

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedInput schema / properties / value / description
      Previous value: -"Value to set in the blackboard (as string, converted by key type)"New value: +"Value as a string, converted by key type: \"42\", \"0.5\", \"true\" or \"1\", a name, an enum index, a vector \"X=1 Y=2 Z=3\", a rotator \"P=0 Y=90 R=0\", an object or class path. Omitted means empty (0, false, none)."
  2. First observedv1.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: writes are not read back (set is always true), unparsable numbers/vectors silently become 0, changes are runtime-only and never persisted, and it is confined to the editor world and not PIE. This is exactly the silent-failure and persistence behavior an agent needs and cannot get from the hints alone.

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?

Front-loaded with verb and scope, then tight sentences on failure behavior, persistence, and world scope, followed by a returns block. Every sentence carries load with no padding.

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?

Covers the mutation's silent-failure semantics, runtime-only nature, editor-world constraint, verification path, and even documents the return shape despite no output schema. Nothing needed to call it correctly 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%, so the schema already documents value conversion format, key_name, and actor_name in detail. The description adds only the phrase 'converting the value string by key type', which largely duplicates the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (write) plus resource and scope (one key of the running blackboard of an editor-world actor), and names the verifying sibling get_blackboard_value. An agent can distinguish it from add_blackboard_key or set_blackboard_key_subsettings without opening 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?

Provides clear context: 'editor world only, never PIE' and 'Runtime state only, nothing saved', plus a directive to verify with get_blackboard_value. It does not name a when-not alternative beyond the get tool, but the operational context 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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