Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add perniemann/pnCore --skill pn-unreal-devgit clone --depth 1 https://github.com/perniemann/pnCoreWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/perniemann/pncore/pn-unreal-dev)<a href="https://agentmods.dev/skills/perniemann/pncore/pn-unreal-dev"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-unreal-dev/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/perniemann/pncore/pn-unreal-dev"><img src="https://agentmods.dev/badge/skills/perniemann/pncore/pn-unreal-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.03392 |
| Opus 5 | $0.00034 | $0.01696 |
| Sonnet 5 | $0.00014 | $0.00678 |
| Haiku 4.5 | $0.00007 | $0.00339 |
Grade A, and why
pn-unreal-dev scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Unreal Engine development skill
When to use
- Writing or refactoring Unreal C++ code
- Setting up Blueprint conventions and patterns
- Defining asset naming and project structure
- Building Unreal plugins (modules, editor extensions, custom asset types)
- Programmatic or live creation of uassets (materials, Niagara, PCG)
- Automating editor workflows (Python, Editor Utility Widgets, UAT)
- Creating or validating materials, Niagara systems, or PCG graphs
- Optimizing tick, loading, or profiling
C++ patterns
- UPROPERTY macros: Use for replicated, serialized, or Blueprint-exposed properties. Specify
EditAnywhere,BlueprintReadOnly,Replicated, etc. as needed. - UFUNCTION macros: Use for Blueprint-callable or RPC functions. Specify
BlueprintCallable,Server,Client,NetMulticastwhen relevant. - UCLASS macros: Use
UCLASS()withBlueprintType,Config, etc. Inherit fromUObject,AActor,UActorComponent, etc. - Gameplay Framework: Use GameMode (rules), GameState (replicated state), PlayerController (input, UI), Pawn (possessed entity), Character (pawn with capsule). Understand ownership and replication.
- No raw pointers for UObjects: Use
TObjectPtr(UE5) orUPROPERTYfor UObject references so GC can track. Use raw pointers only for non-UObject or temporary scope. - GC-safe patterns: Avoid storing UObject pointers in non-UPROPERTY members; use weak references when needed.
Blueprint conventions
- Naming: Use PascalCase for functions, variables. Prefix:
BP_for Blueprint assets,WBP_for widgets,BPC_for components. - Pure vs impure: Use pure (no side effects) for getters and calculations. Use impure for actions.
- Event dispatchers: Use for decoupled communication. Name events clearly (e.g.
OnHealthChanged,OnGameOver). - Interfaces: Use for cross-cutting behavior (e.g.
Interactable,Damageable). Implement in Blueprint or C++. - Avoid spaghetti: Use function nodes, macros, or C++ for complex logic. Keep graphs readable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 170 lines · 68 tokens per session scan A 6ff955e463a4
pn-unreal-dev is a skill published in the GitHub repository perniemann/pnCore (0 stars, last pushed 4d ago), licensed MIT. It adds 68 tokens to every session and 3,392 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
typescript
TypeScript coding conventions, best practices, and patterns for writing clean, maintainable code.
ax-cpp-ai
Use when writing C++ code with axllm for named deployment profiles, generic provider clients, model selection, OpenAI-compatible calls, Responses, Gemini, Anthropic, routers, and balancers.
ax-cpp-agent
Use when writing C++ code with axllm for agents, child delegation, tools, MCP, citations, persistent playbook learning, stage instructions, runtime state, final typed responses, and direct-respond executor skipping.
ax-cpp-flow
Use when writing C++ code with axllm for flows, nodes, program graphs, nested programs, dynamic options, caching, and optimizer components.
ax-cpp-gen
Use when writing C++ code with axllm for AxGen programs, forward calls, indexed multi-sampling, result pickers, streaming, tools, assertions, traces, usage, and output parsing.
ax-cpp-agent-memory-skills
Use when writing C++ code with axllm for agent memory, recall callbacks, dynamic skill discovery, loaded-skill state, and used-skill tracking.