SKILLEMALL.ai

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Integrate OpenClaw with Unreal Engine 5.x projects, editors, and plugins. Use when an agent needs to inspect or scaffold Unreal Engine automation, create or modify UE5 C++ plugins, expose Blueprint-callable nodes, connect OpenClaw to the editor or a running game, drive editor-side tasks through Unreal Remote Control, or design/version-adapted workflows for Unreal Engine 5.0 and newer.

ClawHub Agent Skills author: droidhackzor v0.1.0 MIT-0 21 files · 1 script body ≈ 2 614 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 49/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (unreal-engine) differs from the folder (openclaw-unreal-engine)
    • 60Tools and files. Uses tools (python, node) that frontmatter does not declare
    • 85Steps. 113 steps, 1 vague phrases
    • 100Failures and branches. 4 branches, has a failure section
    • 100Execution cost. Instruction body is 2614 tokens
    • 100Running it twice. Mutating operations check current state
    • low 10 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 387: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 113 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (15 of 15)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This Unreal integration is purpose-aligned, but it needs review because it handles tokens and can overwrite an existing project plugin with weak safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026