gat-brainstorm
Brainstorm a game idea through one-question-at-a-time designer interviews. Produces game.md, systems-index.md, and art-direction.md, or runs as discussion-only.
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 gat-brainstorm
Wartung
Aktuell
2 Tage seit dem letzten Push
Risiko
Prüfung nötig
Lizenz ist unklar
GitHub-Qualität
57
59/100 Qualität · 68/100 Vertrauen
Abdeckungs-Tags
Review-Notizen
Lizenz ist unklar · Financial research output is not financial advice; require human review before any live investment decision
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
Nur SandboxNützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
Audit
Prüfung nötigMaschinenlesbare Prüfung von Installationsbereitschaft, Sicherheitsmetadaten, Wartung und Akzeptanzrisiko.
OpenAgentSkill Trust Score v5
Menschliche Prüfung vor Installation
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
Stars
57 GitHub-Stars
Repository-Aktivität
57 Stars und 9 Forks
Wartung
2 Tage seit dem letzten Push
Lizenz
Unbekannt
Installieren
npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
Installationssicherheit
Standard-Paket- oder Laufzeit-Installationspfad
Berechtigungsfläche
Shell- oder Befehlsausführung
Agent-Ergebnisse
Noch keine Agent-Ergebnisdaten
Dokumentation
Starker README/SKILL.md-Kontext
Risikoübersicht
Vor Produktion prüfen
- Repository license is unknown, which creates compliance 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 gat-brainstorm
- Richtlinie
- Prüfen
- Menschliche Prüfung
- Ja
Vertrauen und Risiko
- Vertrauen
- 60/100
- Audit
- 74/100
- Risikoebene
- Prüfung nötig
Ergebnis-Loop
- Endpoint
- /api/agent/outcome
- Event-ID
- resolve
- Ergebnisse
- 5
Installationsbefehl
npx skills add Yuki001/game-dev-skills --skill gat-brainstormNicht verwenden, wenn
- Teams, die ein vom Anbieter unterstütztes SLA benötigen
- production agents without a repository review
- Repository license is unknown, which creates compliance ambiguity.
- Hinweise auf Hochrisiko-Berechtigungen: Shell- oder Befehlsausführung
- Lizenz ist unklar
Alternative
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
Alternative
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent-Sicherheit v2
42/100 · Automatische Installation vermeiden
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Hoch
Shell- oder Befehlsausführung
Die Skill-Metadaten verweisen auf Terminal-, CLI-, Shell-, Subprozess- oder Befehlsausführungs-Workflows.
Mittel
Browser automation
Skill may drive a browser or interact with web pages.
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.
- Hinweise auf Hochrisiko-Berechtigungen: Shell- oder Befehlsausführung
- 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-gat-brainstormAgent-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%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve-Text
/api/agent/resolve?task=Use%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Installationsübergabe
/api/skills/yuki001-gat-brainstorm/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 gat-brainstorm in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuki001-gat-brainstorm/install
Install command: npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
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-gat-brainstorm/install
LLM-Textformat
/api/skills/yuki001-gat-brainstorm/install?format=text
Alternativen finden
/api/skills/search?q=gat-brainstorm&limit=3
Agent-Prompt
Use gat-brainstorm for this task. Review https://www.openagentskill.com/api/skills/yuki001-gat-brainstorm/install, then install with: npx skills add Yuki001/game-dev-skills --skill gat-brainstormRegistry-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-gat-brainstorm
LLM-Text
/api/registry/manifest/yuki001-gat-brainstorm?format=text
Installationsalias
/api/registry/install/yuki001-gat-brainstorm
Empfehlen
/api/registry/recommend?task=Use%20gat-brainstorm%20in%20an%20agent%20workflow&limit=3
Agent-Fit
Recherche-Agents
Use-Case-Tags
Plattformen
Claude Code
Audit-Bericht
Prüfung nötig · 74/100
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
- 11 OpenAgentSkill-Interaktionen
zuerst prüfen
- Repository license is unknown, which creates compliance 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
Nur Sandbox
Nützlicher Kandidat mit fehlenden oder gemischten Vertrauenssignalen. Bis der Ergebniszyklus die Passung belegt, in einem isolierten Arbeitsbereich verwenden.
GitHub-Akzeptanz
Prüfen57 GitHub-Stars
Star-/Fork-Aktivität
Prüfen57 Stars und 9 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbar
Aktuelle Wartung
Bestanden2 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, which creates compliance ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- Lizenz ist unklar
- Quality score needs review
- GitHub adoption: 57 GitHub stars
- Stars/forks activity: 57 stars, 9 forks; issue activity unavailable in current metadata
- License clarity: Unknown
- Noch keine echten Agent-Ergebnisberichte
- Vor unbeaufsichtigter Installation ist menschliche Prüfung erforderlich
Empfohlene Aktion
Nur in einer Sandbox ausführen und nahe Alternativen vergleichen, bevor sie produktiv eingesetzt wird.
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.
Publish consistently
Content automation
I need my agent to turn research and product updates into useful content drafts.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
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.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
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
GPT Researcher
Run autonomous deep research over web and local sources
DeepResearch
Tongyi Deep Research, the Leading Open-source Deep Research Agent
Übersicht
--- name: gat-brainstorm description: "Brainstorm a game idea through one-question-at-a-time designer interviews. Produces game.md, systems-index.md, and art-direction.md, or runs as discussion-only." argument-hint: "[<hint> | discuss]" user-invocable: true allowed-tools: Read, Glob, Grep, Write, Edit, Agent, AskUserQuestion ---
# Brainstorm
This skill explores a game concept through open-ended designer interview. Spawn `gat-designer` for design reasoning and `gat-artist` for visual direction. Pick questions from the angle table below — follow the conversation, not a script.
## Phase 1: Resolve Mode
- If argument is `discuss` → Mode: `discuss` (no files written, exploration only) - If argument is a hint or empty → Mode: `design` (produces foundational design docs and global art direction)
Check whether `gat/overview/game.md`, `gat/overview/systems-index.md`, or `gat/overview/art-direction.md` already exist. If so, note them — the interview may refine or replace existing decisions instead of starting from scratch.
## Phase 2: The Interview
### Core Rules
- **One question at a time.** Never batch. Wait for the answer before the next question. - **Provide a recommended answer** with each question. Explain the design reasoning. - **Prefer open-ended questions.** Let the user type free-form responses. Reserve `AskUserQuestion` (multiple-choice) for when you are presenting concrete solution options and need the user to pick one. Most of the interview should be dialogue, not forms. - **Pick angles, don't follow steps.** Use the angle table as a menu. Jump to whatever dimension is most useful next — chase what's interesting or ambiguous. - **If a question can be answered by reading existing design files, read them instead of asking.** - **Spawn `gat-designer`** when you need a design reasoning pass: drafting a core loop, proposing systems, evaluating a trade-off, or checking consistency. - **Spawn `gat-artist`** when visual identity needs synthesis: art references, palette, readability, asset groups, production standards, or conflicts between style and gameplay clarity.
### Drilling into Vague Ideas
When the user has a fuzzy idea — about the whole game or a single system — your job is to make it concrete through relentless, curious questioning. This is the core of the interview.
**How to drill:**
- When the user says something vague ("combat should feel impactful"), ask what specifically makes it impactful — is it animation, sound, damage numbers, controller rumble, enemy reaction, time-to-kill? Keep asking until the abstraction bottoms out in concrete mechanics. - When the user proposes a system, ask about its boundaries. What does it NOT do? What system owns the adjacent responsibility? A system without edges is still fuzzy. - When the user describes a player experience ("I want the player to feel lost"), ask what the game does to create that feeling. What does the player see, hear, and do? What information is withheld? What mechanics produce the emotion? - When the user references another game ("like Dark Souls but..."), isolate what exactly they want to keep and what they want to change. The reference is a shortcut — unpack it. - Ask about edge cases and failure states. What happens when the player ignores the system? What happens when they optimize it to the extreme? The answers reveal whether the system is understood or still hazy. - Ask about the player's moment-to-moment decisions. If the user can't describe what choices the player makes inside the system, the system isn't clear yet. - If an answer opens three new questions, pick the most foundational one first. Resolve dependencies before details.
**Signals that something is still vague and needs more drilling:**
- The user uses abstract adjectives without mechanics behind them ("fun", "smooth", "deep", "cool") - A system is named but its inputs, outputs, and rules are undefined - Two systems have overlapping or unclear boundaries - The user can describe what the system IS but not what the player DOES in it - Numbers are absent where they matter (how many? how long? how much?)
### Seed Extraction
If a concept hint was provided, first spawn `gat-designer` to extract what the hint already answers. Briefly summarize what's established so the user can confirm or correct before diving in. Skip if no hint.
### Interview Angles
Pick questions from any angle below. There is no fixed order — follow the thread that matters most at each moment. The table is a palette, not a checklist.
| # | Angle | Purpose | Example prompts | |---|-------|---------|-----------------| | 1 | **Genre & Style** | Establish the game's design identity and reference points | What genre(s) does this live in? What games should it feel like mechanically? Real-time or turn-based? 2D or 3D? Single-player, co-op, or competitive? | | 2 | **Visual Direction** | Establish the global art identity that will become `art-direction.md` | What should the game look like at a glance? Which art references fit or should be avoided? What palette, shape language, camera, readability, and production constraints matter? | | 3 | **Core Player Verb** | Pin down the primary action the player repeats | What does the player actually DO moment-to-moment — shoot, build, explore, talk, craft, steer, command? What makes that action satisfying? | | 4 | **Target Feeling** | Define the emotional experience | What should the player feel during play — tension, mastery, wonder, power, relaxation, social connection, fear, curiosity? When do they feel it most? | | 5 | **Fantasy & Role** | Clarify who the player is in the world | What fantasy does the game fulfill? Who is the player — hero, commander, survivor, creator, investigator, merchant? | | 6 | **Scope & Constraints** | Set boundaries early | Rough scope (jam, indie, commercial)? Platform? Timeline? Team size? Content rating? Hard constraints? Any visual production constraints like pixel art, low-poly, UI-heavy, asset reuse, or resolution limits? | | 7 | **Core Loop** | Map the repeatable cycle that drives engagement | What's the 30-second loop? The 5-minute loop? The session loop? What pulls the player back in? | | 8 | **Systems & Mechanics** | Explore what systems the game needs | What systems does the core loop imply? Which are essential vs. nice-to-have? What does each system depend on? | | 9 | **Progression & Goals** | Define how the player grows and what they strive for | Short-term goals? Long-term goals? Skill tree or gear-based? Linear or branching? How does difficulty ramp? | | 10 | **Economy & Resources** | Map currencies, sinks, and sources | What resources does the player manage? How are they earned and spent? Is there inflation risk? | | 11 | **Risk & Reward** | Balance tension against payoff | What does the player risk losing? What do they gain for taking risks? Is failure interesting or just punishing? | | 12 | **Player Agency** | How much control and choice the player has | Where do players make meaningful choices? Are choices tactical (moment-to-moment) or strategic (long-term)? Emergent or scripted? | | 13 | **Feedback & Juice** | How the game communicates back to the player | How does the player know they did something right? What visual/audio hooks sell the actions? Screen shake, particles, sound? Which of those hooks should drive the global art direction? | | 14 | **Onboarding & Clarity** | How the player learns the game | Tutorial or discovery? How do you teach without lecturing? What's the first thing a new player does? What must be readable instantly in the UI or scene? | | 15 | **Narrative & World** | Story, setting, and tone | Is there a story? Player-driven or authored? What's the tone? How does the world reinforce the mechanics and visual identity? | | 16 | **Multiplayer & Social** | Other humans in the experience | Cooperative, competitive, or solo with social features? Synchronous or asynchronous? How do players interact? | | 17 | **Replayability & Depth** | What keeps players coming back | Procedural generation, build variety, difficulty modes, secrets? What's different on run #2 vs. run #50? | | 18 | **Accessibility** | Who can play and how | Difficulty options? Color independence? Remappable controls? Reaction-time accommodations? What visual signals must not rely on color alone? | | 19 | **Monetization** | Business model (if applicable) | Premium, F2P, subscription? If F2P, what's sold and does it affect gameplay? Any dark patterns to avoid? | | 20 | **Platform & Controls** | Input method and platform constraints | Mouse/keyboard, controller, touch? How many buttons does the design assume? Platform-specific constraints? | | 21 | **Content Volume** | How much stuff the game needs | How many levels, enemies, items, abilities? Is content hand-crafted, procedural, or both? What's the MVP slice? Which asset groups must be planned globally? |
### Navigating the Interview
- **Start where the energy is.** If the user leads with a mechanic, start at Systems. If they describe a feeling, start at Target Feeling. If they mention a reference game, start at Genre & Style. - **Drill, don't move on.** When the user gives a vague or high-level answer, stay on that thread. Ask the follow-up that forces them to be specific. See "Drilling into Vague Ideas" above — this is where most of the value comes from. - **Dive when something is interesting.** A throwaway answer about "the world is post-apocalyptic" might open a rich thread about Narrative & World, Economy (scarcity), or Fantasy & Role. Follow it. - **Ask open-ended, resolve with options.** Most questions should be free-form dialogue — the user types their thoughts. Use `AskUserQuestion` only when you have 2-3 concrete design proposals and need the user to choose among them (e.g. picking a core loop direction, choosing between two system architectures). - **Spawn `gat-designer` mid-interview** when you need to synthesize answers into a concrete proposal (core loop draft, system list, trade-off analysis). Present what the agent returns, then ask about it. - **Spawn `gat-artist` mid-interview** when the visual identity is too vague or conflicting. Ask for a concise art-direction proposal: references, palette, shape language, readability priorities, asset groups, and production limits. Present the proposal, then ask the user what to keep or change. - **Loop back naturally.** If a later answer contradicts an earlier assumption, point it out and resolve the tension. Don't pretend consistency exists when it doesn't. - **Know when to stop.** The interview has covered enough when: - The core loop is clear and the user can describe it in their own words - The system list is named with rough dependencies - The global visual direction has references, palette or mood, readability priorities, and asset group strategy - Scope boundaries are set - The user starts repeating themselves rather than adding new information
## Phase 3: Write or Summarize
### If Mode is `design`
Before writing, summarize what's been decided across gameplay, systems, scope, and visual direction. Ask:
> "Ready to write the design docs?" > Options: `Yes, write them` / `Let me keep discussing`
If yes, read templates: - `.claude/docs/templates/design/game-overview.md` - `.claude/docs/templates/design/systems-index.md` - `.claude/docs/templates/design/global-art.md`
**Step 1** — Spawn `gat-designer` to write both foundational design files in one pass: - `gat/overview/game.md` - `gat/overview/systems-index.md`
Pass all interview answers, the confirmed system list with dependencies, and the game overview and systems index templates.
Instruct the designer to populate the **Key Design Decisions** section in `game.md`: record each foundational choice as a short paragraph, and add a **Why:** note when the rationale or rejected alternatives need to be stated — drawing from the interview's tension-re
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
- 74/100
- 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 gat-brainstorm, bereit für einen manuellen X-Post.
A practical pick for design or creative work: gat-brainstorm: Brainstorm a game idea through one-question-at-a-time designer interviews. Produces game.md, systems-index.md, and art-dire... 57 stars https://www.openagentskill.com/skills/yuki001-gat-brainstorm?ref=x
Optionale Antwort mit Installationsbefehl
Listing + install path for gat-brainstorm: https://www.openagentskill.com/skills/yuki001-gat-brainstorm?ref=x Install: npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
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-gat-brainstorm)
[](https://www.openagentskill.com/skills/yuki001-gat-brainstorm)
[](https://www.openagentskill.com/skills/yuki001-gat-brainstorm/audit)
[](https://www.openagentskill.com/skills/yuki001-gat-brainstorm)Autor
Yuki001
@yuki001
Tags
Plattform-Fit
Gesundheitssignale
- GitHub-Stars
- 57
- Qualitätswert
- 35/100
- Letzter GitHub-Push
- 20. Aug. 2026
- Framework-Hinweise
- Unbekannt
- OpenAgentSkill-Aufrufe
- 11
- 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
Nur Sandbox
- GitHub-Akzeptanz57 GitHub-StarsPrüfen
- Star-/Fork-Aktivität57 Stars und 9 Forks; Issue-Aktivität ist in den aktuellen Metadaten nicht verfügbarPrüfen
- Aktuelle Wartung2 Tage seit dem letzten PushBestanden
- LizenzklarheitUnbekanntPrüfen
- README/SKILL.md-VollständigkeitMetadaten enthalten ausreichend Nutzungs- und Workflow-KontextBestanden
- Abhängigkeits-/LaufzeitrisikoKeine wesentlichen Abhängigkeitsrisikohinweise in öffentlichen MetadatenBestanden
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