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
Asset-Profil
Recherche und Wissensarbeit
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Szenario
Recherche-Agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent-Fit
Claude Code + CLI + Codex
Geeignet für Codex, Claude Code, Cursor, CLI oder benutzerdefinierte Agents.
Installieren
Bereit
npx skills add Yuki001/game-dev-skills --skill game-architect
Wartung
Aktuell
3 Tage seit dem letzten Push
Risiko
Prüfung nötig
Lizenz ist unklar
GitHub-Qualität
57
59/100 Qualität · 65/100 Vertrauen
Abdeckungs-Tags
Review-Notizen
Lizenz ist unklar · Permission surface may require sandboxing
Agent-Adoptionskarte
Vertrauen, Audit und Installationsbereitschaft auf einen Blick
Diese Werte kombinieren öffentliche Repository-Metadaten, OpenAgentSkill-Reviewsignale, Wartungsaktualität und Installationsbereitschaft. Sie helfen bei der Vorauswahl, ersetzen aber keine menschliche Prüfung.
Qualität
VielversprechendUseful candidate, but compare it with alternatives before adopting.
Vertrauen
Do not auto-installTrust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
Audit
Prüfung nötigMaschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
OpenAgentSkill Trust Score v5
Menschliche Prüfung vor Installation
Choose a stronger alternative or inspect the source manually before any install attempt.
Stars
57 GitHub-Stars
Repository-Aktivität
57 Stars und 9 Forks
Wartung
3 Tage seit dem letzten Push
Lizenz
Unbekannt
Installieren
npx skills add Yuki001/game-dev-skills --skill game-architect
Installationssicherheit
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsfläche
shell or command execution, filesystem or document access
Agent-Ergebnisse
Noch keine Agent-Ergebnisdaten
Dokumentation
Starker README/SKILL.md-Kontext
Risikoübersicht
Vor Produktion prüfen
- 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.
- Lizenz ist unklar
- Quality score needs review
Installationsbereitschaft
Installationspfad verfügbar
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Lizenz ist unklar
- Noch keine Agent-Proven-Ergebnisbelege
Agent-lesbare Metadaten
Maschinenlesbare Entscheidungsdaten für diesen Skill.
Nutze diesen Block oder das eingebettete JSON, um zu entscheiden, ob ein Agent diesen Skill installieren, eine Alternative wählen oder zuerst menschliche Prüfung anfordern soll.
Geeignete Aufgaben
- Research-Agent-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
- Suchquellen
Geeignete Agents
Installationsentscheidung
- Befehl
- npx skills add Yuki001/game-dev-skills --skill game-architect
- Richtlinie
- Blockieren
- Menschliche Prüfung
- Ja
Vertrauen und Risiko
- Vertrauen
- 57/100
- Audit
- 72/100
- Risikoebene
- Prüfung nötig
Ergebnis-Loop
- Endpoint
- /api/agent/outcome
- Event-ID
- resolve
- Ergebnisse
- 5
Installationsbefehl
npx skills add Yuki001/game-dev-skills --skill game-architectNicht verwenden, wenn
- Teams, die ein vom Anbieter unterstütztes SLA benötigen
- production agents without a repository review
- Repository license is unknown; missing explicit license file may cause legal ambiguity.
- Hinweise auf Hochrisiko-Berechtigungen: Shell or command execution, Secrets or environment access
- Lizenz ist unklar
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Agent-Sicherheit v2
28/100 · Automatische Installation vermeiden
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.
Hoch
Shell- oder Befehlsausführung
Die Skill-Metadaten verweisen auf Terminal-, CLI-, Shell-, Subprozess- oder Befehlsausführungs-Workflows.
Mittel
Netzwerkzugriff
Die Skill ruft wahrscheinlich Remote-Seiten, APIs, Repositories oder externe Dienste ab.
Mittel
Dateisystemzugriff
Die Skill kann Projektdateien, Dokumente, generierte Artefakte oder den lokalen Arbeitsbereich lesen oder schreiben.
Hoch
Secrets or environment access
Skill metadata references credentials, tokens, environment variables, or secret-bearing workflows.
- Hinweise auf Hochrisiko-Berechtigungen: Shell or command execution, Secrets or environment access
- Lizenz ist unklar
Installationsziele
Diesen Skill im Agent-Workflow installieren
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
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-architectAgent-Auflösungsplan
Lass einen Agent die Eignung vor der Installation prüfen.
Die Resolve API liefert die beste Skill, Alternativen, Sicherheitsrichtlinien, Auditnotizen, Installationsziel und einen direkt nutzbaren Prompt.
JSON öffnen
/api/agent/resolve?task=Use%20game-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve-Text
/api/agent/resolve?task=Use%20game-architect%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Installationsübergabe
/api/skills/yuki001-game-architect/install
Agent sollte prüfen
- 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.
Prompt kopieren
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.Agent-Übergabe
Gib dem Agent den Installationspfad, nicht noch ein Verzeichnis.
Über den öffentlichen Endpunkt erhältst du Befehl, Sicherheitscheckliste, Ziel-Prompts und kanonische Links.
Installationsübergabe
/api/skills/yuki001-game-architect/install
LLM-Textformat
/api/skills/yuki001-game-architect/install?format=text
Alternativen finden
/api/skills/search?q=game-architect&limit=3
Agent-Prompt
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-architectRegistry-Metadaten
Agent-lesbares Profil für die automatische Skill-Auswahl.
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Manifest
/api/registry/manifest/yuki001-game-architect
LLM-Text
/api/registry/manifest/yuki001-game-architect?format=text
Installationsalias
/api/registry/install/yuki001-game-architect
Empfehlen
/api/registry/recommend?task=Use%20game-architect%20in%20an%20agent%20workflow&limit=3
Agent-Fit
Recherche-Agents
Plattformen
Claude Code
Audit-Bericht
Prüfung nötig · 72/100
Maschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
Agent-Entscheidungspanel
Fallback candidate for Research agents
Prototype with this skill first; keep a fallback candidate ready.
Rolle im Stack
Fallback-Kandidat
Primäre Eignung
Recherche-Agents
Vertrauenslabel
Zuerst prototypisieren
Installationspfad
Befehl bereit
Verwenden wenn
- Research-Agent-Workflows
- Claude-Code-Teams
- builders willing to evaluate younger projects
Evidenz
- recent repository activity
- install command or GitHub repo available
- Qualitätsprofil 59/100
- 7 OpenAgentSkill-Interaktionen
zuerst prüfen
- Repository license is unknown; missing explicit license file may cause legal ambiguity.
Implementierungspfad
- 1Installieren Sie es in einem Sandbox-Agent und führen Sie eine Recherche-Agents-Aufgabe vollständig aus.
- 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.
Vertrauensprofil
Do not auto-install
Trust Score v5 found insufficient evidence for agent installation. Treat this as discovery material, not an executable recommendation.
GitHub-Akzeptanz
Prüfen57 GitHub-Stars
Star-/Fork-Aktivität
Prüfen57 Stars und 9 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden3 Tage seit dem letzten Push
Lizenzklarheit
PrüfenUnbekannt
Positive Signale
- KI-Prüfung genehmigt
- Installationspfad ist verfügbar
- Repository-Belege sind verfügbar
- Kürzlich gewartetes Repository
- Der Installationsbefehl weist kein offensichtliches Hochrisikomuster auf
- Ergebniszyklus ist bereit, benötigt aber den ersten echten Agent-Lauf
Vor Installation prüfen
- 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.
- Lizenz ist unklar
- 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
- Noch keine echten Agent-Ergebnisberichte
- Vor unbeaufsichtigter Installation ist menschliche Prüfung erforderlich
Empfohlene Aktion
Choose a stronger alternative or inspect the source manually before any install attempt.
Qualitätsprofil
Vielversprechend Kandidat für Agent-Workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow-Eignung
Diese Skill in diesen Szenarien nutzen
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.
Workflow-Eignung
Zum vollständigen Workflow hinzufügen
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.
Alternativen-Shortlist
Vor Installation vergleichen
Similar skills that may fit this task.
Last30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
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DeepResearch
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Übersicht
--- 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 |
---
Technische Details
- Version
- 1.0.0
- Lizenz
- Unknown
- Letzte Aktualisierung
- 20. Aug. 2026
- Veröffentlicht
- 20. Aug. 2026
Entscheidungsübersicht
Fallback-Kandidat
recent repository activity
Audit
Installationsprüfung
Installations- und Adoptionsprüfung
- Sicherheit
- 71/100
- Wartung
- 100/100
- Installieren
- 92/100
Von Agent belegte Evidenz
Von Agent belegte Evidenz
Ergebnisberichte nach Resolve, Prüfung, Installation und einem begrenzten Lauf.
- Erfolgsrate
- —
- Letzter Fehler
- —
- Ergebnisse
- 0
- Ausgabequalität
- —
- Fehlgeschlagen
- 0
- Nicht relevant
- 0
- Installationen
- 0
- Durch Risiko blockiert
- 0
- Einrichtung erforderlich
- 0
- Produktion
- 0
Noch keine Agent-Ergebnisdaten. Der erste Lauf kann Erfolg, Einrichtungsbedarf, Risikoblockaden, Fehler oder Irrelevanz über /api/agent/outcome melden.
Installieren
Zum Agent-Workflow hinzufügen
Kostenlos und Open Source. Bericht vor der Installation in Produktions-Agents prüfen.
Wachstums-Loop
Share-Kit
Szenariobasierter Entwurf für game-architect, bereit für einen manuellen X-Post.
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
Optionale Antwort mit Installationsbefehl
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
Quelle des Eintrags
Registry-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- Yuki001
- Quelle
- Yuki001/game-dev-skills
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
Diesen Skill beanspruchenEigentümeranspruch
Diesen Skill-Eintrag beanspruchen
Dieser Registry-indexiert-Eintrag wird Yuki001 zugeschrieben, ist aber noch nicht offiziell markiert. Beanspruche ihn, um ein verifiziertes Eigentümersignal hinzuzufügen und künftige Launch-, Installations- und Audit-Updates vertrauenswürdiger zu machen.
Creator-Backlink-Kit
Evidenz-Badges in deine README einfügen
Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
[](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)Autor
Yuki001
@yuki001
Tags
Plattform-Fit
Gesundheitssignale
- GitHub-Stars
- 57
- Qualitätswert
- 35/100
- Letzter GitHub-Push
- 20. Aug. 2026
- Framework-Hinweise
- Unbekannt
- OpenAgentSkill-Aufrufe
- 7
- Installationskopien
- 0
- Externe Klicks
- 0
Community-Signal
Teile mit, ob dieser Skill für deinen Agent-Workflow nützlich ist. Zusammengefasstes Feedback verbessert das Ranking im Laufe der Zeit.
Vertrauen & Sicherheit
Do not auto-install
- GitHub-Akzeptanz57 GitHub-StarsPrüfen
- Star-/Fork-Aktivität57 Stars und 9 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarPrüfen
- Aktuelle Wartung3 Tage seit dem letzten PushBestanden
- LizenzklarheitUnbekanntPrüfen
- README/SKILL.md-VollständigkeitMetadaten enthalten ausreichend Nutzungs- und Workflow-KontextBestanden
- Abhängigkeits-/Laufzeitrisikodatabase surfaceBestanden
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