「prototype」の検索結果

Design game experience, systems, and levels. Converge the chosen concept into one GAME_DESIGN defining the player promise, core loop, how the world responds, the systems actually needed, level pacing, feedback, failure, and a fully playable prototype. Use for design the game world, deepen the gameplay and levels, write the game design document, design the branching story structure, scenes, dialogue and consequences. 游戏体验、系统与关卡策划。把选定概念收束为一份 GAME_DESIGN，定义玩家承诺、核心循环、世界响应、必要系统、关卡节奏、反馈、失败和可完整游玩的原型。用于设计游戏世界、深化玩法和关卡、设计互动叙事的场景对白与分支因果等需求。

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Turn a novel into a fully playable game on the selected target platform. Orchestrates the whole adaptation pipeline — requirements intake, gameable deconstruction, concept selection, world and visual design, target-runtime build, and evidence-based QA — for a novel in any language. Use for novel to game, story to game, book to game, adapt this novel into a game, turn this book into a playable prototype, make an interactive story or text adventure from this novel. NovelToGame 总入口。把任意语言的原始小说、拆文库或 oh-story 写作工程转成有原著依据、可在目标平台完整游玩的游戏，编排游戏化拆解、概念选择、游戏与视觉设计、目标运行环境构建和证据化质量验证。用于小说转游戏、把这本书做成游戏、把小说改成互动小说 / 互动叙事 / 文字冒险游戏等需求。

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Build a risk-matched whitebox or the approved production game for its target runtime. Turn GAME_DESIGN, and ART_DIRECTION when production begins, into a minimal BUILD_BRIEF and a runnable candidate that can be iterated with replayable evidence. Use for prototype the riskiest design question, implement the approved game design, or turn this design into a running game. 游戏构建执行。先按最大风险做白盒，或在正式生产时把批准后的 GAME_DESIGN 与 ART_DIRECTION 压缩成最小 BUILD_BRIEF，在目标运行环境中实现可运行候选并用可回放证据迭代。用于验证高风险设计问题、构建游戏原型或实现批准方案。

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Generate a small app or tool and deploy it live to Vercel via API

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Execution-gap audit - cross-references the startup idea backlog against shipped skills, prototypes, and cross-repo PRs, surfacing the top 3 ideas to build next by narrative and operator fit.

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Build, inspect, update, restore, or share Avibe Show Pages for visual explanations, diagrams, reports, or interactive prototypes. Covers the page workspace and its Git history.

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Dung khi can TAO RA anh hoac prompt anh bang AI — anh thuong hieu ca nhan, logo, key visual campaign, anh dang hang ngay, editorial, infographic, mockup web, quote graphic. Tu doc brand identity trong context roi dung prompt, gen anh hoac xuat prompt cho MidJourney, DALL-E, Imagen, Leonardo. Co che do nhan anh reference va tra ve master prompt copy-paste duoc. Kich hoat khi user nhac 'thiet ke anh', 'lam logo', 've banner', 'prompt MidJourney', 'tao key visual', 'lam anh giong anh nay', 'gen anh AI', 'doi mau thuong hieu tren anh'. Khong dung cho — viet brief giao designer lam thi dung skill 42-brief-hinh-anh; quy trinh asset ca campaign thi dung skill 41-campaign-asset-list; video avatar AI thi dung skill 24-ai-avatar-production; UI wireframe tuong tac thi dung web-prototype; animation thi dung motion-frames.

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Turn a customer problem into distinct ideas, a small prototype and a measurable learning test. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.

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This skill should be used when the user asks about "ralph arguments", "quick mode", "commit spec", "max iterations", "ralph state file", "prototype overlay", "execution modes", "ralph loop", "coordinator behavior", "delegate to subagent", or needs guidance on Ralph plugin arguments, state management, delegation patterns, or execution loop behavior. Core behavioral skill for all Ralph Specum operations.

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Use only when the user explicitly invokes `$ralph-specum`, requests Ralph Specum in Codex, or asks Ralph Specum to handle a named phase or optional prototype.

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Clone any website into a pixel-perfect single-file HTML prototype. Extracts design tokens, assets, CSS computed styles, interaction patterns, and content via Playwright. Outputs a self-contained HTML file with real data injection. Use when the user wants to clone, replicate, reverse-engineer, or create a pixel-perfect copy of any website or web app. Provide one or more target URLs as arguments.

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构建一个可抛弃的原型来回答设计问题。当用户想验证状态模型或逻辑是否合理，或探索 UI 应该长什么样时使用。

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Use when building or reviewing Micronaut applications — Micronaut.run bootstrap, @Singleton/@Prototype, @Factory beans, @ConfigurationProperties, environments, @Requires, @Controller vs services, @Scheduled, graceful shutdown, @ExecuteOn for blocking work, and Jakarta-consistent APIs. This should trigger for requests such as Review Java code for Micronaut application structure and beans; Apply best practices for Micronaut configuration, @Requires, and factories; Improve scheduling, shutdown, or threading in Micronaut services. ; Review Micronaut dependency injection scopes and factories; Configure Micronaut @Requires conditions for environments. Part of Plinth Toolkit

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Runs a product quality review on a journey, feature, landing page, onboarding flow, or AI/agent surface and returns a friction log, a scored critical-journey review, and a taste bar your team can calibrate against. Use when someone asks is this good enough to ship, how polished should it be, why do users bounce, what is our quality bar, how do we build taste, or to review a design, prototype, onboarding, or checkout. Draws on 264 insights from 100 Lenny's Podcast guests incl. Katie Dill, Dylan Field and Stewart Butterfield.

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Trigger for: Other Transaction or OT should-cost, cost estimate, cost-share analysis, milestone pricing, funding profile, proposed-price comparison, prototype price analysis, research OT budget, production follow-on OT estimate, or OT price-reasonableness support under 10 U.S.C. 4021 or 4022. Build auditable milestone-based .xlsx workbooks using BLS OEWS wages, CALC+ positioning, GSA Per Diem, materials, cost sharing, and agreement-specific fees. Use for pre-solicitation budgets and proposal comparisons. Do NOT use for FAR-based IGCEs, OT project descriptions, grants, or an Agreements Officer's determination. Requires the bls-oews, gsa-calc, and, when travel applies, gsa-perdiem MCP servers.

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Use when auditing source code for vulnerabilities — drive CodeQL/Semgrep/Joern to taint untrusted data source-to-sink across injection, memory safety, deserialization/prototype-pollution, secrets/crypto/authz/race, and supply-chain risks

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Use when pentesting a web application or API — injection, XSS/CSP, SSRF/cloud-metadata, HTTP desync & cache poisoning, SSTI/prototype-pollution/deserialization, JWT/OAuth/GraphQL/IDOR, business logic & single-packet race

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Use only when the user explicitly invokes grill-for-unknowns or asks for a map-vs-territory unknowns pass, blindspot discovery, unknown-known prototypes, or a subagent launch packet before implementation.

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Build multiple genuinely different versions of a UI piece you describe, rendered behind a visual picker so you can flip through them live and promote the one that feels right. Only runs when explicitly invoked; it does not trigger on its own.

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Package a finished piece of work (spec, prototype, implementation notes) into a single document that gets reviewers to understanding and approval fast. Use when the user needs buy-in, a review, or a shareable summary of what was built and why.

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Routes Alibi users to the right explanation, confidence, prototype, or optional-backend workflow and points them to the bundled helpers needed to run it.

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Scaffold or standardize a production-ready repository structure with specs, source layout, tests, CI, agent context, config examples, release notes, and operational docs. Use when starting a new repo, turning a prototype into a maintainable project, adding missing repository foundations, or creating a repo skeleton before implementation. For AGENTS.md-only context scaffolding, use agentsmd-scaffold.

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当用户要做/研究一个东西、想提升某个技能、或觉得某个产出不够好想改进时使用。用「改良主义」先逼出一个最垃圾但能跑的原型，再引导他自己洞察缺陷、提出问题，提改良假说→实践检验→迭代，信奉「洞察缺陷 > 如何优化 > 最终答案」，并把每次改进的方法本身沉淀成方法论。触发场景：要做 X、研究 X、提升 X、X 做得不好想改进、怎么优化 X、不知从哪下手做。

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用户学任何新概念/新技术/新理论的默认深度入口——一次性用五个视角把概念讲透并帮他选深入方向：crossover 用已会的撬动、occam 框定该学多深、graph 建知识地图、prototype 最小原型迭代、feynman 拷问检验。触发场景：我想学 X、理解 X、X 是什么、讲讲 X、搞懂 X、学一下 X、深入 X、给我讲讲 X。除非用户明确只要某一个视角（那时改用对应的单个 learn-* skill）。

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