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CD unreal-skill

Use this skill when creating, editing, or reviewing an Unreal Engine Agent Skill, a named bundle of instructions registered with the unreal-mcp server (distinct from Claude Code's harness skills under `.claude/skills/`). Trigger when the user wants to add or change a skill that the in-editor agent will load. Concrete triggers: 'create a new Agent Skill', 'add a skill for X workflow', 'edit/update this skill', 'review my skill', 'make a Python skill class', 'create a skill UAsset', 'register a skill so Claude picks it up'; writing or editing a `SKILL.md` inside a UE plugin's `Skills/` or `Python/skills/` folder; defining a Python skill class registered with the skill registry; calling `CreateSkill`, `ListSkills`, or `GetSkills` MCP tools; designing a skill's name, description, or instruction body. SKIP for: authoring a toolset (use create-toolset), invoking an existing skill at runtime (use unreal-mcp), editing harness-level Claude Code skills under `.claude/skills/` or `~/.claude/skills/`, or generic uses of the word 'skill'.

EpicGames/unreal-engine-skills-for-claude-code-plugin Agent Skills author: EpicGames 1 file body ≈ 1 466 tokens Open the sourcegithub.com↗ analyzed 14 h ago

Use this skill when creating, editing, or reviewing an Unreal Engine Agent Skill, a named bundle of instructions registered with the unreal-mcp server…

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
82/100
safety, quality, tests
Safety 60%
100
Quality 40%
56
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Shorten the description to 1024 characters.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-long description is 1041 chars, limit 1024

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
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 5 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 13 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1466 tokens

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)
  • +3Description length 1041: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.