Ue Gameplay Architecture Planning logo

Ue Gameplay Architecture Planning

Community
kevinpbuckley
ue-gameplay-architecture-planning

Design and plan Unreal Engine gameplay systems before implementation. Turns an ambiguous feature or game idea into an Unreal-native architecture with explicit ownership, lifetime, Actor/Component/UObject/Subsystem choices, Game Framework placement, C++ versus Blueprint boundaries, communication and replication flows, data and asset models, trade-off analysis, and an ordered implementation plan. Use when brainstorming a new mechanic or system, comparing architectural approaches, deciding where logic or state should live, mapping a feature across gameplay classes, or preparing a safe task list for an implementation agent.

Overview

Publisherkevinpbuckley
Repositoryunreal-engine-skills
Skill nameue-gameplay-architecture-planning
Stars
89
Forks
9
Bundled files
1
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by kevinpbuckley on GitHub. Read the source before you install it.

Installation

Install the Ue Gameplay Architecture Planning AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kevinpbuckley/unreal-engine-skills/tree/master/skills/core/ue-gameplay-architecture-planning
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kevinpbuckley/unreal-engine-skills.git /tmp/unreal-engine-skills
mkdir -p .claude/skills
cp -r /tmp/unreal-engine-skills/skills/core/ue-gameplay-architecture-planning .claude/skills/ue-gameplay-architecture-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ue Gameplay Architecture Planning in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ue Gameplay Architecture Planning on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ue Gameplay Architecture Planning is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Gameplay architecture planning

Convert a feature request into a concrete Unreal Engine design before code or asset work begins. The result should reduce implementation ambiguity without inventing abstractions the project does not need.

This is an architecture and planning skill, not a mandatory gate. If the user asked only for a design, stop at the design. If the user also asked for implementation, perform the design pass briefly and continue within the authorized scope.

When to use this skill

  • Brainstorming a gameplay feature, game system, prototype, or project architecture.
  • Deciding between Actor, Component, UObject, Subsystem, Game Framework, or asset-based designs.
  • Mapping ownership, lifetime, persistence, authority, replication, and communication.
  • Defining the C++/Blueprint boundary and designer-facing asset workflow.
  • Comparing viable approaches and producing an ordered implementation plan.

Do not activate it for a localized bug fix or a mechanical edit whose architecture is already settled.

The Unreal planning model

Do not translate another engine's scene tree literally. An Unreal design usually spans several independent structures:

  1. World hierarchy — Actors and attached Scene Components.
  2. Behavior composition — Actor Components owned by Actors.
  3. Gameplay ownership — GameMode, GameState, PlayerController, PlayerState, Pawn/Character, and GameInstance.
  4. Services — Engine, GameInstance, World, and LocalPlayer Subsystems.
  5. Data and assets — Data Assets, Data Tables, config, soft references, and SaveGame objects.
  6. Communication — direct calls, interfaces, delegates/Event Dispatchers, Gameplay Messages, replicated properties, and RPCs.

Treat these as separate decisions. A feature can have an Actor hierarchy, state owned by a PlayerState component, definitions stored in Primary Data Assets, and UI notified through a local delegate at the same time.

Read references/decision-matrices.md when choosing among these types or when the feature crosses networking, persistence, UI, or level travel.

Workflow

1. Establish the decision-changing constraints

Inspect the existing project first when it is available. Reuse its modules, base classes, subsystems, naming, asset patterns, and networking model unless there is a concrete reason to change them.

Clarify only facts that would materially change the architecture. If safe assumptions allow progress, state them and continue. High-value questions usually concern:

  • Target UE version and platforms.
  • Single-player, listen server, dedicated server, or peer-hosted multiplayer.
  • Who owns authority and which state every client must observe.
  • Whether state survives pawn replacement, level travel, reconnects, or application restarts.
  • Expected scale: player count, active instances, update frequency, and world size.
  • Whether designers need Blueprint extension, data-only tuning, or runtime authoring.
  • Existing framework commitments such as GAS, CommonUI, Gameplay Messages, Mass, or a project plugin architecture.

Do not ask for preferences that can be derived from the project or resolved by a clearly superior default.

2. Define responsibilities before selecting classes

Break the feature into responsibilities such as:

  • authoritative rules and validation;
  • replicated or local runtime state;
  • world representation and collision;
  • reusable behavior;
  • static definitions and designer-authored tuning;
  • persistence;
  • presentation and UI;
  • asynchronous loading or background work.

Give each responsibility one clear owner. Avoid using the same class merely because it is easy to access globally.

3. Compare real alternatives

When multiple approaches are genuinely viable, present two or three. Compare them against the feature's actual constraints:

  • lifetime and ownership fit;
  • authority and replication cost;
  • coupling and testability;
  • Blueprint/design workflow;
  • performance and scale;
  • save/load and travel behavior;
  • implementation complexity and migration cost.

Recommend one option and explain why it wins here. Do not manufacture alternatives when the correct Unreal pattern is unambiguous.

4. Produce the architecture maps

Map the chosen design across the dimensions that apply:

Responsibility and lifetime map

ResponsibilityUnreal owner/typeLifetimeAuthority/replicationReason
...............

Object and component map

Show Actor ownership and Scene Component attachment as a compact tree. List non-scene UObjects, Actor Components, Subsystems, widgets, and assets separately so the tree does not imply ownership that does not exist.

Communication map

For every important flow, state sender, receiver, mechanism, payload, authority, and timing. An RPC crosses the network; a delegate notifies local listeners; a replicated property represents durable shared state. They are not interchangeable.

Data map

Separate immutable definitions, mutable runtime state, replicated state, saved state, and presentation-only state. Identify hard versus soft asset references when loading behavior matters.

C++/Blueprint boundary

Put stable rules, authority checks, replication, reusable primitives, and performance-sensitive logic in C++. Use Blueprint for composition, presentation, asset assignment, designer extension, and intentionally exposed events. State the exact extension seams rather than saying "hybrid."

5. Sequence implementation as vertical slices

Produce an ordered task list that leaves the project in a coherent, testable state after each phase. Prefer a thin end-to-end path before breadth.

A useful sequence is:

  1. Define data contracts, interfaces, tags, and module/plugin dependencies.
  2. Implement the smallest authoritative runtime path.
  3. Add one representative asset or Blueprint composition.
  4. Connect presentation through a local notification boundary.
  5. Add replication and persistence deliberately, if required.
  6. Cover failure paths, cleanup, and lifecycle transitions.
  7. Add automation, multiplayer PIE scenarios, profiling, and packaging checks proportional to risk.

For every task, name the expected files or Unreal asset types, prerequisites, observable result, and verification. Mark decisions that must be validated in a prototype before downstream work.

Required output quality

A complete architecture response should contain, when relevant:

  1. Goal, constraints, and assumptions.
  2. Recommended architecture in a short decision summary.
  3. Alternatives and trade-offs.
  4. Responsibility/lifetime and object/component maps.
  5. Communication, authority, and replication flow.
  6. Data, asset, persistence, and loading model.
  7. Explicit C++/Blueprint boundary.
  8. Ordered implementation plan with verification checkpoints.
  9. Risks, open decisions, and conditions that would change the recommendation.

Scale the response to the feature. A small mechanic may need a one-page design; a cross-level multiplayer system may need all nine sections.

Architectural guardrails

  • Do not turn GameInstance into a global gameplay-state container. It is local and does not replicate.
  • Do not place durable player state on a Pawn if it must survive death or repossession.
  • Do not use GameMode for client-visible state; GameMode exists only on the authority.
  • Do not introduce a Subsystem only to avoid passing a reference. Its lifetime must match the service it owns.
  • Do not make every domain object an Actor. Use Actors for world identity, transform, networking, or ticking that genuinely needs world participation.
  • Do not use Tick as the default communication mechanism. Prefer events, timers, or explicit state transitions.
  • Do not use RPCs as local event dispatchers or delegates as network transport.
  • Do not duplicate authoritative state in widgets. UI observes gameplay state and derives display state.
  • Do not recommend GAS, Mass, Gameplay Messages, or a plugin boundary solely because they are scalable. Adopt them when their capabilities match demonstrated requirements.
  • Do not design only the happy path. Include teardown, unbinding, travel, disconnect, respawn, asset-load failure, and authority rejection where applicable.

Version notes

Target UE 5.8 APIs and terminology. Flag any recommendation that depends on an experimental plugin or on behavior that differs across UE 5.x. Do not fall back to UE4-era defaults such as legacy input, PhysX, World Composition, or raw UObject member pointers when the modern UE5 pattern is relevant.

Related skills

Use the relevant domain skills to substantiate the final design, especially: ue-gameplay-framework, ue-actors-and-components, ue-subsystems, ue-delegates-and-events, ue-networking-and-replication, ue-data-driven-design, ue-asset-management, ue-save-and-load, ue-blueprint-fundamentals, ue-blueprint-cpp-integration, ue-project-structure, and ue-automation-and-testing.

References & source material

UE 5.8 engine source:

  • Engine/Source/Runtime/Engine/Classes/GameFramework/Actor.h — AActor world identity, lifecycle, ownership, replication, and ticking.
  • Engine/Source/Runtime/Engine/Classes/Components/ActorComponent.h and Components/SceneComponent.h — behavior composition versus transform hierarchy.
  • Engine/Source/Runtime/Engine/Classes/GameFramework/GameModeBase.h, GameStateBase.h, PlayerController.h, PlayerState.h, and Pawn.h — gameplay ownership and network roles.
  • Engine/Source/Runtime/Engine/Classes/Engine/GameInstance.h — application and travel lifetime.
  • Engine/Source/Runtime/Engine/Public/Subsystems/Subsystem.h — subsystem base and lifecycle.
  • Engine/Source/Runtime/Engine/Classes/Engine/DataAsset.h — UDataAsset and UPrimaryDataAsset definitions.
  • Engine/Source/Runtime/Engine/Classes/GameFramework/SaveGame.h — persistent save object.
  • Engine/Source/Runtime/Net/Core/Classes/Net/Serialization/FastArraySerializer.h — delta serialization option for replicated collections.

Detailed selection guidance: references/decision-matrices.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ue Gameplay Architecture Planning AI skill do?

Design and plan Unreal Engine gameplay systems before implementation. Turns an ambiguous feature or game idea into an Unreal-native architecture with explicit ownership, lifetime, Actor/Component/UObject/Subsystem choices, Game Framework placement, C++ versus Blueprint boundaries, communication and replication flows, data and asset models, trade-off analysis, and an ordered implementation plan. Use when brainstorming a new mechanic or system, comparing architectural approaches, deciding where logic or state should live, mapping a feature across gameplay classes, or preparing a safe task lis...

Why use Ue Gameplay Architecture Planning on TypingMind?

Because you install it once and use it with any model. Ue Gameplay Architecture Planning is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ue Gameplay Architecture Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kevinpbuckley/unreal-engine-skills/tree/master/skills/core/ue-gameplay-architecture-planning. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ue Gameplay Architecture Planning?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ue Gameplay Architecture Planning?

As many as you like. As long as a model supports skills, you can use Ue Gameplay Architecture Planning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ue Gameplay Architecture Planning AI skill free?

It is published on GitHub by kevinpbuckley. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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