game-architect
READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Work
Profil de l’actif
Recherche et travail de connaissance
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scénario
Agents de recherche
I need my agent to research a topic, compare sources, and produce a concise report.
Adéquation Agent
Claude Code + CLI + Codex
Compatible avec Codex, Claude Code, Cursor, CLI ou des Agents personnalisés.
Installer
Prêt
npx skills add Yuki001/game-dev-skills --skill game-architect
Maintenance
À jour
3 jours depuis le dernier push
Risque
Revue nécessaire
La licence est ambiguë
Qualité GitHub
57
59/100 Qualité · 65/100 Confiance
Tags de couverture
Notes de revue
La licence est ambiguë · Permission surface may require sandboxing
Carte d’adoption Agent
Confiance, audit et préparation à l’installation en un coup d’œil
Ces scores combinent les métadonnées publiques du dépôt, les signaux de revue OpenAgentSkill, la fraîcheur de maintenance et la préparation à l’installation. Ils servent à présélectionner et ne remplacent pas la revue humaine.
Qualité
PrometteurUseful candidate, but compare it with alternatives before adopting.
Confiance
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Revue nécessaireRevue lisible par machine de la préparation à l’installation, des métadonnées de sécurité, de la maintenance et du risque d’adoption.
Trust Score OpenAgentSkill v5
Revue humaine avant installation
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
57 stars GitHub
Activité du dépôt
57 stars et 9 forks
Maintenance
3 jours depuis le dernier push
Licence
Inconnu
Installer
npx skills add Yuki001/game-dev-skills --skill game-architect
Sécurité d’installation
Chemin d’installation standard de package ou runtime
Surface de permissions
shell or command execution, filesystem or document access
Résultats Agent
Pas encore de données de résultats Agent
Documentation
Contexte README/SKILL.md solide
Résumé des risques
Revoir avant production
- Repository license is unknown; missing explicit license file may cause legal ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- La licence est ambiguë
- Quality score needs review
Préparation à l’installation
Chemin d’installation disponible
- Le chemin d’installation est disponible
- La preuve du dépôt est disponible
- La licence est ambiguë
- Pas encore de preuve de résultat Agent-Proven
Métadonnées lisibles par Agent
Données de décision lisibles par machine pour ce skill.
Utilisez ce bloc ou le JSON intégré pour décider si un Agent doit installer ce skill, choisir une alternative ou demander d’abord une revue humaine.
Tâches adaptées
- Workflows d’Agents de recherche
- Équipes Claude Code
- builders willing to evaluate younger projects
- Sources de recherche
Agents adaptés
Décision d’installation
- Commande
- npx skills add Yuki001/game-dev-skills --skill game-architect
- Politique
- Bloquer
- Revue humaine
- Oui
Confiance et risque
- Confiance
- 57/100
- Audit
- 72/100
- Niveau de risque
- Revue nécessaire
Boucle de résultat
- Endpoint
- /api/agent/outcome
- ID d’événement
- resolve
- Résultats
- 5
Commande d’installation
npx skills add Yuki001/game-dev-skills --skill game-architectNe pas utiliser quand
- Équipes qui nécessitent un SLA soutenu par le fournisseur
- production agents without a repository review
- Repository license is unknown; missing explicit license file may cause legal ambiguity.
- Indices de permissions à haut risque : Shell or command execution, Secrets or environment access
- La licence est ambiguë
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Sécurité Agent v2
28/100 · Éviter l’installation automatique
This skill should not be selected by an agent without explicit human security review.
Do not auto-install. Inspect the source, dependencies, and permission surface first.
Élevé
Exécution shell ou de commande
Les métadonnées de la skill font référence à des workflows de terminal, CLI, shell, sous-processus ou exécution de commande.
Moyen
Accès réseau
La skill récupère probablement des pages distantes, API, dépôts ou services externes.
Moyen
Accès au système de fichiers
La skill peut lire ou écrire des fichiers de projet, documents, artefacts générés ou l’état local de l’espace de travail.
Élevé
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Indices de permissions à haut risque : Shell or command execution, Secrets or environment access
- La licence est ambiguë
Cibles d’installation
Installer ce skill dans votre workflow Agent
Utilisez le point de terminaison public pour récupérer la commande, la checklist, les prompts et les liens canoniques.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install yuki001-game-architectPlan de résolution Agent
Laissez un Agent vérifier la pertinence avant l’installation.
L’API Resolve renvoie la skill sélectionnée, des alternatives, la politique de sécurité, les notes d’audit, la cible d’installation et un prompt prêt à l’emploi.
Ouvrir JSON
/api/agent/resolve?task=Use%20game-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Texte Resolve
/api/agent/resolve?task=Use%20game-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Relais d’installation
/api/skills/yuki001-game-architect/install
L’Agent doit vérifier
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copier le prompt
Task: Use game-architect in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20game-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuki001-game-architect/install
Install command: npx skills add Yuki001/game-dev-skills --skill game-architect
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Relais Agent
Donnez à l’Agent le chemin d’installation, pas un autre annuaire.
Utilisez le point de terminaison public pour récupérer la commande, la checklist, les prompts et les liens canoniques.
Relais d’installation
/api/skills/yuki001-game-architect/install
Format texte LLM
/api/skills/yuki001-game-architect/install?format=text
Trouver des alternatives
/api/skills/search?q=game-architect&limit=3
Prompt Agent
Use game-architect for this task. Review https://www.openagentskill.com/api/skills/yuki001-game-architect/install, then install with: npx skills add Yuki001/game-dev-skills --skill game-architectMétadonnées Registry
Profil lisible par Agent pour la sélection automatique de skills.
L’API Registry fournit les signaux de décision, confiance, audit, cas d’usage et installation sans analyser l’interface.
Manifest
/api/registry/manifest/yuki001-game-architect
Texte LLM
/api/registry/manifest/yuki001-game-architect?format=text
Alias d’installation
/api/registry/install/yuki001-game-architect
Recommander
/api/registry/recommend?task=Use%20game-architect%20in%20an%20agent%20workflow&limit=3
Adéquation Agent
Agents de recherche
Tags de cas d’usage
Plateformes
Claude Code
Rapport d’audit
Revue nécessaire · 72/100
Revue lisible par machine de la préparation à l’installation, des métadonnées de sécurité, de la maintenance et du risque d’adoption.
Panneau de décision Agent
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Rôle dans la pile
Candidate de secours
Pertinence principale
Agents de recherche
Libellé de confiance
Prototyper d’abord
Chemin d’installation
Commande prête
À utiliser lorsque
- Workflows d’Agents de recherche
- Équipes Claude Code
- builders willing to evaluate younger projects
Preuves
- recent repository activity
- install command or GitHub repo available
- profil qualité 59/100
- 7 événements OpenAgentSkill
revoir d’abord
- Repository license is unknown; missing explicit license file may cause legal ambiguity.
Chemin d’implémentation
- 1Installez-le dans un Agent en sandbox et exécutez une tâche de Agents de recherche de bout en bout.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Profil de confiance
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Adoption GitHub
Vérifier57 stars GitHub
Activité stars/forks
Vérifier57 stars et 9 forks; l’activité des issues n’est pas disponible dans les métadonnées actuelles
Maintenance récente
Validé3 jours depuis le dernier push
Clarté de licence
VérifierInconnu
Signaux positifs
- Revue IA approuvée
- Le chemin d’installation est disponible
- La preuve du dépôt est disponible
- Dépôt maintenu récemment
- La commande d’installation ne présente aucun motif de haut risque évident
- La boucle de résultats est prête mais nécessite la première exécution réelle de l’Agent
Réviser avant installation
- Repository license is unknown; missing explicit license file may cause legal ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- La licence est ambiguë
- Quality score needs review
- Permission surface needs review: shell or command execution, filesystem or document access
- GitHub adoption: 57 GitHub stars
- Stars/forks activity: 57 stars, 9 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Permission surface: shell or command execution, filesystem or document access
- Pas encore de rapports de résultats Agent réels
- Une revue humaine est requise avant une installation sans surveillance
Action recommandée
Choose a stronger alternative or inspect the source manually before any install attempt.
Profil qualité
Prometteur candidat pour les workflows Agent
Useful candidate, but compare it with alternatives before adopting.
Adéquation au workflow
Utilisez cette skill dans ces scénarios
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Adéquation au workflow
Ajouter à un workflow complet
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Design, build, test, and ship interfaces
Frontend and UI
A practical workflow for agents that turn product briefs or Figma designs into polished frontend code, review the result, test it in a browser, and prepare a safe deployment.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Liste d’alternatives
Comparer avant installation
Similar skills that may fit this task.
Last30days Skill
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Vue d’ensemble
--- name: game-architect description: READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Works as a domain knowledge plugin alongside workflow skills (OpenSpec, SpecKit) or plan mode of an agent. ---
# Game Architect Skill
Game architecture domain knowledge reference. Provides paradigm selection, system design references for game project architecture.
> [!NOTE] > This skill contains **domain knowledge only**, not a workflow. Pair it with a workflow skill (e.g., OpenSpec, SpecKit) or an agent's plan mode for structured design flow.
## Usage Modes
### With Workflow Skill (Recommended)
When used with a workflow skill (e.g., OpenSpec, SpecKit) or in the plan mode of an agent, this skill serves as a domain knowledge plugin:
- **During requirements/spec phases**: Consult the Paradigm Selection Guide and System-Specific References to inform architectural decisions - **During design/planning phases**: Use the Reference Lookup Guide below to read relevant `references/` documents
### Knowledge Mode (Query)
When user requests to query knowledge for game architecture, this skill provides a reference lookup guide to relevant `references/` documents based on the task.
---
## Reference Lookup Guide
When designing game architecture, read the relevant `references/` documents based on the task:
### Architecture References
| When | Read | |------|------| | Always (high-level structure) | `references/macro-design.md` | | Always (core principles) | `references/principles.md` | | Requirement analysis | `references/requirements-analysis.md` | | Choosing DDD paradigm | `references/domain-driven-design.md` | | Choosing Data-Driven paradigm | `references/data-driven-design.md` | | Choosing Prototype paradigm | `references/prototype-design.md` | | Evolution & extensibility review | `references/evolution.md` | | Changing requirements in an existing implementation | `references/requirement-change-strategy.md` | | Performance optimization needed | `references/performance-optimization.md` | | Multiplayer support needed | `references/multiplayer-overview.md` |
- For physical architecture design, see the Physical Architecture References table below. - For system-specific design, see the System-Specific References table below. - For multiplayer system design, see the Multiplayer References table below.
Note : Only read the multiplayer references when multiplayer is needed.
### Physical Architecture References
| When | Read | |------|------| | Project structure & file organization | `references/project-structure.md` | | Data formats, processing, custom formats, bundles, metadata | `references/data-files.md` | | Gameplay content editor applications and authoring pipelines | `references/content-editor.md` | | Asset conventions & pipeline | `references/asset-conventions.md` | | Distribution, packaging, hot update, CDN, deployment | `references/distribution.md` |
### System-Specific References
| System Category | Reference | |----------------|-----------| | Foundation & Core (Logs, Timers, Modules, Events, Resources, Audio, Input) | `references/system-foundation.md` | | Time & Logic Flow (Update Loops, Async, FSM, Command Queues, Controllers) | `references/system-time.md` | | Combat & Scene (Scene Graphs, Spatial Partitioning, ECS/EC, Loading) | `references/system-scene.md` | | UI & Modules (Modules Management, MVC/MVP/MVVM, UI Management, Data Binding, Reactive) | `references/system-ui.md` | | Skill System (Attribute, Skill, Buff) | `references/system-skill.md` | | Action Combat System (HitBox, Damage, Melee, Projectiles) | `references/system-action-combat.md` | | Camera, Character & Controller 3C (PlayerController, Physics, Camera, Actor States) | `references/system-3c.md` | | Effect & Feedback System (Screen Shake, VFX, Hit-Stop, Haptics, SFX, Floating Text, UI Feedback, Orchestration) | `references/system-effect-feedback.md` | | Narrative System (Dialogue, Cutscenes, Story Flow) | `references/system-narrative.md` | | Game AI System (Movement, Pathfinding, Decision Making, Tactical) | `references/system-game-ai.md` | | Mod & DLC System (Plugin Architecture, Config Database, Scripting, Hooks, Extensibility) | `references/system-mod.md` | | Procedural Content Generation (PCG) (World/Level Generation, Roguelike, Noise, Simulation) | `references/system-pcg.md` | | Algorithm & Data Structures (Pathfinding, Search, Physics, Generic Solver) | `references/algorithm.md` | | Puzzle Game System (Match-3, Jigsaw, Water Sort, Blocks, Physics Puzzles, Board Games, Content & Presentation Boundaries) | `references/system-puzzle.md` |
### Multiplayer References
| Focus | Reference | Use When | |------|------|------| | Multiplayer overview | `references/multiplayer-overview.md` | Decide client/server responsibility, authority split, and gameplay sync style | | Multiplayer protocol and connection | `references/multiplayer-protocol.md` | Design messages, serialization, Req/Resp/Notify, heartbeat, reconnect | | Multiplayer server architecture | `references/multiplayer-server-architecture.md` | Design ownership boundaries, process roles, deployment, persistence, recovery | | Common server components and services | `references/multiplayer-implementation-common.md` | Build shared infrastructure such as auth, gateway, connector, db, cache, discovery, queue, observability | | Room server build playbook | `references/multiplayer-implementation-room.md` | Build a concrete small-to-medium room-based realtime server with join flow, room ownership, settlement, reconnect | | Encounter server build playbook | `references/multiplayer-implementation-encounter.md` | Build a concrete turn-based or combat-workflow server with checkpointing, idempotent actions, settlement | | Persistent world server build playbook | `references/multiplayer-implementation-world.md` | Build a concrete AOI world server with region ownership, transfer, location registry, reconnect | | Deterministic sync, lockstep, and rollback | `references/multiplayer-deterministic-sync.md` | Design deterministic input-sync architectures, frame pipelines, rollback, replay, and desync handling | ---
## Paradigm Selection Guide
| Paradigm | KeyPoint | Applicability Scope | Examples | Reference | | :--- | :--- | :--- | :--- | :--- | | **Domain-Driven Design (DDD)** | OOP & Entity First | High Rule Complexity. <br> Rich Domain Concepts. <br> Many Distinct Entities. | Core Combat Logic, Physics Interactions, Damage/Buff Rules, Complex AI Decision. | `references/domain-driven-design.md` | | **Data-Driven Design** | Data Layer First | High Content Complexity. <br> Flow Orchestration. <br> Simple Data Management. | **Content**: Quests, Level Design.<br>**Flow**: Tutorial Flow, Skill Execution, Narrative.<br>**Mgmt**: Inventory, Shop, Mail, Leaderboard. | `references/data-driven-design.md` | | **Use-Case Driven Prototype** | Use-Case Implementation First | Rapid Validation | Game Jam, Core Mechanic Testing. | `references/prototype-design.md` |
Here, **Data-Driven Design** means a **data-structure-first programming paradigm**, not specifically configuration-driven gameplay. See `references/data-driven-design.md` for the full terminology boundary.
### Mixing Paradigms
Most projects mix paradigms: 1. **Macro Consistency**: All modules follow the same Module Management Framework. 2. **Domain for Core Entities & Rules**: Use DDD for systems with high rule complexity, rich domain concepts, and many distinct entities (e.g., Combat Actors, Damage Formulas, AI Decision). 3. **Data for Content, Flow & State**: Use Data-Driven for expandable content (Quests, Level Design), flow orchestration (Tutorial, Skill Execution, Narrative), and simple data management (Inventory, Shop). 4. **Hybrid Paradigms**: - 4.1 **Entities as Data**: Domain Entities naturally hold both data (fields) and behavior (methods). Design entities to be serialization-friendly (use IDs, keep state as plain fields) so they serve both roles without a separate data layer. - 4.2 **Flow + Domain**: Use data-driven flow to orchestrate the sequence/pipeline, domain logic to handle rules at each step. E.g., Skill System: flow drives cast→channel→apply, domain handles damage calc and buff interactions. - 4.3 **Separate Data/Domain Layers**: Only when edit-time and runtime representations truly diverge. Use a Bake/Compile step to bridge them. E.g., visual node-graph editors, compiled assets. 5. **Paradigm Interchangeability**: Many systems can be validly implemented with either paradigm. E.g., Actor inheritance hierarchy (Domain) ↔ ECS components + systems (Data-Driven); Buff objects with encapsulated rules (Domain) ↔ Tag + Effect data entries resolved by a generic pipeline (Data-Driven). See **Selection Criteria** table above for trade-off signals. 6. **Integration**: Application Layer bridges different paradigms.
### Selection Criteria
When both DDD and Data-Driven fit, use these signals:
| Signal | Favor DDD | Favor Data-Driven | |--------|-----------|-------------------| | Entity interactions | Complex multi-entity rules (attacker × defender × buffs × environment) | Mostly CRUD + display, few cross-entity rules | | Behavior source | Varies by entity type, hard to express as pure data | Driven by config tables, designer-authored content | | Change frequency | Rules change with game balance iterations | Content/flow changes far more often than logic | | Performance profile | Acceptable overhead for rich object graphs | Needs batch processing, cache-friendly layouts | | Networking | Stateful objects acceptable | Flat state snapshots preferred (sync, rollback) | | Team workflow | Programmers own the logic | Designers need to iterate without code changes |
---
Détails techniques
- Version
- 1.0.0
- Licence
- Unknown
- Dernière mise à jour
- 20 août 2026
- Publié
- 20 août 2026
Instantané de décision
Candidate de secours
recent repository activity
Audit
Revue d’installation
Revue d’installation et d’adoption
- Sécurité
- 71/100
- Maintenance
- 100/100
- Installer
- 92/100
Preuves validées par Agent
Preuves validées par Agent
Rapports après resolve, revue, installation et une exécution limitée.
- Taux de réussite
- —
- Échec récent
- —
- Résultats
- 0
- Qualité de sortie
- —
- Échecs
- 0
- Non pertinent
- 0
- Installations
- 0
- Bloqué par le risque
- 0
- Configuration requise
- 0
- Production
- 0
Aucune donnée de résultat Agent pour l’instant. La première exécution peut signaler succès, besoin de configuration, blocage de risque, échec ou non-pertinence via /api/agent/outcome.
Installer
Ajouter au workflow Agent
Gratuit et open source. Examinez le rapport avant l’installation dans des Agents de production.
Boucle de croissance
Kit de partage
Brouillon guidé par scénario pour game-architect, prêt pour une publication manuelle sur X.
game-architect: READ this skill when designing or planning any game system architecture — including combat, s... 57 stars https://www.openagentskill.com/skills/yuki001-game-architect?ref=x
Réponse facultative avec commande d’installation
Listing + install path for game-architect: https://www.openagentskill.com/skills/yuki001-game-architect?ref=x Install: npx skills add Yuki001/game-dev-skills --skill game-architect
Source de la fiche
Indexé par Registry
Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.
- Créateur
- Yuki001
- Source
- Yuki001/game-dev-skills
- Indexé par
- Index communautaire OpenAgentSkill
L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.
Revendiquer ce skillRevendication du propriétaire
Revendiquer cette fiche de skill
Cette fiche Indexé par Registry est attribuée à Yuki001, mais n’est pas encore marquée officielle. Revendiquez-la pour ajouter un signal de propriétaire vérifié et rendre les futures mises à jour de lancement, d’installation et d’audit plus fiables.
Kit de backlinks créateur
Ajoutez les badges de preuve à votre README
Affichez la fiche canonique, les signaux actuels de confiance et d’audit, ainsi que de vraies preuves Agent-Proven là où les développeurs évaluent le dépôt.
[](https://www.openagentskill.com/skills/yuki001-game-architect)
[](https://www.openagentskill.com/skills/yuki001-game-architect)
[](https://www.openagentskill.com/skills/yuki001-game-architect/audit)
[](https://www.openagentskill.com/skills/yuki001-game-architect)Auteur
Yuki001
@yuki001
Tags
Adéquation plateforme
Signaux de santé
- Stars GitHub
- 57
- Score de qualité
- 35/100
- Dernier push GitHub
- 20 août 2026
- Indications de framework
- Inconnu
- Vues OpenAgentSkill
- 7
- Copies d’installation
- 0
- Clics sortants
- 0
Signal de communauté
Indiquez si ce skill semble utile à votre workflow Agent. Les retours agrégés améliorent le classement au fil du temps.
Confiance et sécurité
Do not auto-install
- Adoption GitHub57 stars GitHubVérifier
- Activité stars/forks57 stars et 9 forks; l’activité des issues n’est pas disponible dans les métadonnées actuellesVérifier
- Maintenance récente3 jours depuis le dernier pushValidé
- Clarté de licenceInconnuVérifier
- Complétude README/SKILL.mdLes métadonnées incluent suffisamment de contexte d’usage et de workflowValidé
- Risque dépendances/runtimedatabase surfaceValidé
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