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.
供给资产档案
研究与知识工作
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
场景
研究 Agent
I need my agent to research a topic, compare sources, and produce a concise report.
适配 Agent
Claude Code + CLI + Codex
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
维护状态
新鲜
距上次推送 2 天
风险
需审查
许可证不清晰
GitHub 质量
57
59/100 质量 · 68/100 信任
覆盖标签
审查说明
许可证不清晰 · Financial research output is not financial advice; require human review before any live investment decision
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
仅限沙盒有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
Stars
57 个 GitHub Stars
仓库活跃度
57 个 Star,9 个 Fork
维护状态
距上次推送 2 天
许可证
未知
安装
npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
安装安全性
标准软件包或运行时安装路径
权限范围
Shell 或命令执行
Agent 结果
暂未有 Agent 结果数据
文档
README/SKILL.md 上下文充分
风险摘要
生产前审查
- Repository license is unknown, which creates compliance ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- 许可证不清晰
- Quality score needs review
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 许可证不清晰
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- 检索来源
适用 Agent
安装决策
- 命令
- npx skills add Yuki001/game-dev-skills --skill gat-brainstorm
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 60/100
- 审计
- 74/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- Repository license is unknown, which creates compliance ambiguity.
- 高风险权限提示:Shell 或命令执行
- 许可证不清晰
替代 Skill
Last30days Skill
53.5K Stars
npx skills add mvanhorn/last30days-skill -g
替代 Skill
Academic Research Skills
38.4K Stars
npx skills add Imbad0202/academic-research-skills
替代 Skill
GPT Researcher
28.0K Stars
npx skills add assafelovic/gpt-researcher
替代 Skill
DeepResearch
19.8K Stars
npx skills add Alibaba-NLP/DeepResearch
Agent 安全 v2
42/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
高
Shell 或命令执行
Skill 元数据引用了终端、CLI、Shell、子进程或命令执行工作流。
中
Browser automation
Skill may drive a browser or interact with web pages.
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
- 高风险权限提示:Shell 或命令执行
- 许可证不清晰
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
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 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20gat-brainstorm%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/yuki001-gat-brainstorm/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
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 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/yuki001-gat-brainstorm/install
LLM 文本格式
/api/skills/yuki001-gat-brainstorm/install?format=text
寻找替代方案
/api/skills/search?q=gat-brainstorm&limit=3
Agent 提示词
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 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Agent 决策面板
Fallback candidate for Research agents
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
研究 Agent
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- 研究 Agent 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 59/100 质量档案
- 11 个 OpenAgentSkill 交互事件
先审查
- Repository license is unknown, which creates compliance ambiguity.
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次研究 Agent任务。
- 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.
信任档案
仅限沙盒
有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
GitHub 采用度
检查57 个 GitHub Stars
Star/Fork 活跃度
检查57 个 Star,9 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过距上次推送 2 天
许可证清晰度
检查未知
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- Repository license is unknown, which creates compliance ambiguity.
- Financial research output is not financial advice; require human review before any live investment decision.
- 许可证不清晰
- 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
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
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.
工作流匹配
加入完整工作流
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.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
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
概览
--- 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
技术详情
- 版本
- 1.0.0
- 许可证
- Unknown
- 最近更新
- 2026年8月20日
- 发布时间
- 2026年8月20日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 gat-brainstorm 准备的场景化草稿,可手动发布到 X。
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
可选:带安装命令的回复
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
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- Yuki001
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 Yuki001,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](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)作者
Yuki001
@yuki001
平台适配
健康信号
- GitHub Stars
- 57
- 质量评分
- 35/100
- 最近 GitHub 推送
- 2026年8月20日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 11
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
仅限沙盒
- GitHub 采用度57 个 GitHub Stars检查
- Star/Fork 活跃度57 个 Star,9 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护距上次推送 2 天通过
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