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.
공급 자산 프로필
리서치 및 지식 작업
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
시나리오
리서치 Agent
I need my agent to research a topic, compare sources, and produce a concise report.
Agent 적합도
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI 또는 맞춤형 Agent에 적합합니다.
설치
준비됨
npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
유지보수
최신
마지막 푸시 후 3일
위험
검토 필요
라이선스가 명확하지 않습니다
GitHub 품질
57
59/100 품질 · 68/100 신뢰
커버리지 태그
검토 메모
라이선스가 명확하지 않습니다 · Financial research output is not financial advice; require human review before any live investment decision
Agent 채택 스코어카드
신뢰, 감사, 설치 준비 상태를 한눈에 확인하세요
이 점수는 공개 저장소 메타데이터, OpenAgentSkill 검토 신호, 유지보수 최신성, 설치 준비 상태를 결합합니다. 후보 선정 신호일 뿐, 사람의 검토를 대체하지 않습니다.
품질
유망유용한 후보이지만 채택 전에 대안과 비교하세요.
신뢰
샌드박스 전용신뢰 신호가 부족하거나 혼재된 유용한 후보입니다. 결과 루프가 작업 적합성을 입증할 때까지 격리된 작업 공간에서 사용하세요.
감사
검토 필요설치 준비 상태, 보안 메타데이터, 유지보수 및 채택 위험에 대한 기계 판독형 검토입니다.
OpenAgentSkill 신뢰 점수 v5
설치 전 사람 검토
실제 작업에 사용하기 전 샌드박스에서만 실행하고 유사 대안과 비교하세요.
스타
GitHub 스타 57
저장소 활동
스타 57, 포크 9
유지보수
마지막 푸시 후 3일
라이선스
알 수 없음
설치
npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
설치 안전성
표준 패키지 또는 런타임 설치 경로
권한 범위
Shell 또는 명령 실행
Agent 결과
아직 Agent 결과 데이터가 없습니다
문서
README/SKILL.md 맥락이 충분합니다
위험 요약
프로덕션 전 검토
- Repository license is unknown, which creates compliance ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- 라이선스가 명확하지 않습니다
- Quality score needs review
설치 준비 상태
설치 경로 사용 가능
- 설치 경로를 사용할 수 있습니다
- 저장소 근거를 사용할 수 있습니다
- 라이선스가 명확하지 않습니다
- 아직 Agent 검증 결과 근거가 없습니다
Agent 읽기용 메타데이터
이 스킬의 기계 판독형 의사결정 데이터.
이 블록 또는 포함된 JSON을 사용해 Agent가 이 스킬을 설치할지, 대안을 고를지, 먼저 사람의 검토를 요청할지 판단할 수 있습니다.
적합한 작업
- 리서치 Agent 워크플로
- Claude Code 팀
- builders willing to evaluate younger projects
- 검색 소스
적합한 Agent
설치 결정
- 명령어
- npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
- 정책
- 검토
- 사람 검토
- 예
신뢰와 위험
- 신뢰
- 60/100
- 감사
- 74/100
- 위험 수준
- 검토 필요
결과 루프
- 엔드포인트
- /api/agent/outcome
- 이벤트 ID
- resolve
- 결과
- 5
사용하지 말아야 할 경우
- 벤더 지원 SLA가 필요한 팀
- production agents without a repository review
- Repository license is unknown, which creates compliance ambiguity.
- 고위험 권한 힌트: Shell 또는 명령 실행
- 라이선스가 명확하지 않습니다
Agent 안전 v2
42/100 · 자동 설치 피하기
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
높음
Shell 또는 명령 실행
Skill 메타데이터가 터미널, CLI, Shell, 하위 프로세스 또는 명령 실행 워크플로를 참조합니다.
중간
Browser automation
Skill may drive a browser or interact with web pages.
중간
네트워크 접근
Skill은 원격 페이지, API, 저장소 또는 외부 서비스에 접근할 수 있습니다.
중간
파일 시스템 접근
Skill은 프로젝트 파일, 문서, 생성 산출물 또는 로컬 작업 공간 상태를 읽거나 쓸 수 있습니다.
- 고위험 권한 힌트: Shell 또는 명령 실행
- 라이선스가 명확하지 않습니다
설치 대상
Agent 워크플로에 이 스킬 설치
공개 설치 엔드포인트에서 명령어, 안전 체크리스트, 대상 프롬프트와 정규 링크를 가져옵니다.
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 해결 계획
설치 전에 Agent가 적합성을 검증하게 하세요.
Resolve API는 최우선 스킬, 대안, 안전 정책, 감사 메모, 설치 대상 및 Agent가 페이지를 스크래핑하지 않고 사용할 수 있는 프롬프트를 반환합니다.
JSON 열기
/api/agent/resolve?task=Use%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 텍스트
/api/agent/resolve?task=Use%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
설치 핸드오프
/api/skills/yuki001-gat-brainstorm/install
Agent가 확인할 항목
- Resolve API에서 작업 적합도와 대안을 확인합니다.
- 감사 점수, 신뢰 점수 및 안전 정책 경고를 확인합니다.
- Codex, Claude Code, Cursor 또는 CLI의 설치 대상 호환성을 확인합니다.
프롬프트 복사
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 핸드오프
또 다른 디렉터리 페이지 대신 설치 경로를 Agent에게 제공합니다.
공개 설치 엔드포인트에서 명령어, 안전 체크리스트, 대상 프롬프트와 정규 링크를 가져옵니다.
설치 핸드오프
/api/skills/yuki001-gat-brainstorm/install
LLM 텍스트 형식
/api/skills/yuki001-gat-brainstorm/install?format=text
대안 찾기
/api/skills/search?q=gat-brainstorm&limit=3
Agent 프롬프트
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 메타데이터
자동 스킬 선택을 위한 Agent 읽기용 프로필.
Registry API를 통해 동일한 결정, 신뢰, 감사, 사용 사례, 설치 신호를 제공하므로 Agent가 UI를 스크래핑하지 않고도 순위를 매길 수 있습니다.
Agent 결정 패널
Fallback candidate for Research agents
먼저 이 스킬로 프로토타입을 만들고 대체 후보를 준비하세요.
스택 내 역할
대체 후보
주요 적합도
리서치 Agent
신뢰 라벨
먼저 프로토타입
설치 경로
명령어 준비됨
사용 시점
- 리서치 Agent 워크플로
- Claude Code 팀
- builders willing to evaluate younger projects
근거
- 최근 저장소 활동
- 설치 명령 또는 GitHub 저장소를 사용할 수 있습니다
- 품질 프로필 59/100
- OpenAgentSkill 상호작용 11건
먼저 검토
- Repository license is unknown, which creates compliance ambiguity.
구현 경로
- 1샌드박스 Agent에 설치하고 리서치 Agent 작업을 처음부터 끝까지 한 번 실행하세요.
- 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.
신뢰 프로필
샌드박스 전용
신뢰 신호가 부족하거나 혼재된 유용한 후보입니다. 결과 루프가 작업 적합성을 입증할 때까지 격리된 작업 공간에서 사용하세요.
GitHub 채택도
확인GitHub 스타 57
스타/포크 활동
확인스타 57, 포크 9; 현재 메타데이터에서 이슈 활동을 확인할 수 없습니다
최근 유지보수
통과마지막 푸시 후 3일
라이선스 명확성
확인알 수 없음
긍정 신호
- AI 검토 승인됨
- 설치 경로를 사용할 수 있습니다
- 저장소 근거를 사용할 수 있습니다
- 최근 유지보수된 저장소
- 설치 명령에서 뚜렷한 고위험 패턴이 발견되지 않았습니다
- 결과 루프는 준비되었지만 첫 실제 Agent 실행이 필요합니다
설치 전 검토
- Repository license is unknown, which creates compliance ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- 라이선스가 명확하지 않습니다
- 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
- 아직 실제 Agent 결과 보고서가 없습니다
- 무인 설치 전에 사람 검토가 필요합니다
권장 작업
실제 작업에 사용하기 전 샌드박스에서만 실행하고 유사 대안과 비교하세요.
품질 프로필
유망 Agent 워크플로용 후보
유용한 후보이지만 채택 전에 대안과 비교하세요.
워크플로 적합도
이 스킬을 사용할 시나리오
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.
워크플로 적합도
완전한 워크플로에 추가
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.
대안 후보
설치 전 비교
이 작업에 적합할 수 있는 유사 스킬입니다.
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
개요
--- 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
기술 세부 사항
- 버전
- 1.0.0
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- 2026년 8월 20일
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- 2026년 8월 20일
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Agent 검증 증거
Resolve, 검토, 설치 및 한 번의 제한된 실행 후 결과 보고서입니다.
- 성공률
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아직 Agent 결과 데이터가 없습니다. 첫 실행은 /api/agent/outcome을 통해 성공, 설정 필요, 위험 차단, 실패 또는 비관련 결과를 보고할 수 있습니다.
성장 루프
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gat-brainstorm용 시나리오 기반 초안입니다. X에 수동으로 게시할 수 있습니다.
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
선택 사항: 설치 명령이 포함된 답글
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
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개발자가 저장소를 평가하는 위치에 정규 등록, 현재 신뢰 및 감사 신호, 실제 Agent-Proven 증거를 표시합니다.
[](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)작성자
Yuki001
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- 2026년 8월 20일
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- GitHub 채택도GitHub 스타 57확인
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