「raft」の検索結果

Expert guide for modern WebGPU and WebGL 3D graphics in the browser using Three.js (WebGPURenderer + TSL), Babylon.js, PlayCanvas, React Three Fiber (R3F), and 3Dviz spatial reasoning — covers object craft across 3 scales, surface continuity at joins, physical interaction envelopes, grounded scientific visualization, KTX2/Meshopt optimization, and 3D visual anti-slop / Panduan ahli grafis 3D web, WebGPU modern, dan penalaran spasial 3Dviz.

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Plan, script, caption, and publish short-form video for TikTok. Use when the user wants to write the first 1-3 second hook (spoken line plus on-screen text), draft a caption under 2,200 chars with TikTok settings and hashtags, ride a trending sound without being cringe, strip AI tells from a spoken script to sound human on camera, or plan a week around completion rate. TikTok is video-only: the user supplies the video, the skills produce the script, caption, and settings, then publish via Publora.

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Producing digital media -- writing, images, video, audio, presentations, and multimedia -- with an understanding of craft, audience, accessibility, and ethics. Covers composition principles, copyright-safe sourcing, accessibility features (alt text, captions, contrast), remix culture, attribution practices, and the difference between creating for yourself, for a small audience, and for the open web. Use when helping a learner move from media consumer to media producer.

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Crafts professional git commit messages following Conventional Commits. Use when committing changes or writing commit messages.

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Contracts, commercial law, and intellectual property essentials for founders, managers, and knowledge workers. Covers the elements of contract formation, common contract types, property rights, consumer protection, employment law basics, and the four IP regimes — patents, copyrights, trademarks, and trade secrets. Use when drafting or reviewing an agreement, protecting an invention or brand, evaluating a licensing deal, or understanding regulatory exposure.

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Distributed consensus algorithms and logical time for cloud and multi-node systems. Covers Lamport clocks, vector clocks, FLP impossibility, Paxos (basic, multi, fast), Raft, Viewstamped Replication, Byzantine fault tolerance basics, quorum reads/writes (N/R/W), leader election, and TLA+ specification style. Use when designing replicated state machines, picking a consensus protocol, reasoning about split-brain and quorum loss, or writing formal specs for distributed coordination.

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Classical orbital mechanics from Kepler to Hohmann. Covers the six orbital elements, Kepler's three laws, vis-viva, orbit types (circular, elliptical, parabolic, hyperbolic), transfer orbits, gravity assists, the two-body problem, and practical methods for computing ephemerides. Use when reasoning about planet motion, spacecraft trajectories, comet orbits, exoplanet transits, or binary star dynamics.

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Crafts and generates professional conventional commit messages following Angular/Conventional Commits format. Use when committing changes, writing git commit messages, or when user mentions commit message.

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用户在周期性复盘 X 内容数据、分析哪些内容类型表现好、决定下步内容策略调整时使用。四步闭环:数据收集(拉曝光/互动/收藏)→原因分析(按内容类型对比,查Hook/Body/CTA)→优化迭代("如果重来怎么做更好")→记录追踪(Notion模板闭环)。找20%贡献80%价值的内容加倍投入。周复盘聚焦数据(互动率),月复盘审视战略(变现路径)。Trigger signals:"这周发了15条怎么复盘""哪些类型互动高""下周内容策略怎么调""帮我分析数据"/"weekly content review""which content type performs better""optimize next week's content"。不适用于:单条内容生产(用x-short-content-craft)、帖子没爆焦虑心态(用x-longtail-strategy)、理解推荐算法机制(用x-foryou-algorithm)。

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当用户写出的内容读起来像产品公告/官方更新(如"我们发布了X""支持Y功能""效果很好")，需要翻译成读者能拿走的外部语言时调用。也适用于:用户问"怎么把公告式表达改成强推文""这条推文为什么没人理"(若原因是只讲自己不讲读者)、"怎么把功能介绍写得吸引人"。Trigger 词:公告式表达/内部语言/外部语言/帮助式表达/announcement tone/helpful expression/show don't tell/translate to reader value。不适用于:从零起草新内容(用 x-short-content-craft)、检查内容五件套完备性(用 x-five-piece-checklist)、评估内容值不值得发(用 x-four-saves)。

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用户在帖子没爆时感到焦虑、怀疑自己是否适合做 X,或连发一批内容后评估整体表现、设定增长目标时使用。核心认知:公共平台传播是长尾分布(3861 帖均值 188/中位数 42),一条没爆是预期的中位数而非失败;目标不是让每条都爆,而是系统性提高进前 10% 的概率。Trigger signals: "我连发20条只2条过百该放弃吗""怎么让每条都爆""发了这么多没水花""一条没爆就怀疑人生""是不是我不适合做X" / "only 2 out of 20 hit 100, should I quit" "how to make every post go viral" "my posts get no engagement"。不适用于:单条内容生产(用 x-short-content-craft)、数据复盘操作(用 x-data-review)、理解推荐算法机制(用 x-foryou-algorithm)。

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用户审计自己的内容结构占比、判断单条帖子传播上限、或困惑"发了感叹/观点帖没人理"时调用。 关键 trigger: "内容原型/content archetype""哪种内容容易爆/which content goes viral" "传播上限/viral ceiling""普通表达型/资源入口型/工具教程型/AI工具发现型" "为什么没人互动/why no engagement""内容方向有问题/content direction wrong"。 不适用于: 已确定写某种短内容类型并需要组织结构(用 x-short-content-craft)、 检查帖子五件套完备性(用 x-five-piece-checklist)、做账号定位取舍(用 x-positioning-tradeoff)。

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用户要起草一条 X 短内容(推文/帖子)、不知道用什么结构或类型时;或问"怎么发一条教人用 XX 的帖""怎么排版推文能让更多人收藏""what structure should I use for a tweet / how to write a tutorial post"时。先按目标指标选四类型之一(故事→涨粉 / 列表→收藏 / 观点→互动 / 教程→忠诚),再用 Hook-Body-CTA 三段骨架起草;资源/工具类可套爆款公式(工具+场景+三步)。不适用于:已有草稿想检查五件套完备性(→x-five-piece-checklist)、想把公告腔改写成帮助式语言(→x-three-translations)、想按读者功能分类预测传播上限(→x-content-archetypes)、纯信息查询(如推文字数上限)。

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当用户想在大V帖下评论获取曝光、纠结Repost还是Quote、或问"怎么引发互动""怎么在别人帖下获曝光又不被当蹭流量"时调用。六种评论互动法(有价值提问/A-B引战/坎宁汉姆定律/真诚请教/生活日常/找骂)+高质量回复吃原帖流量+Repost vs Quote区分。Trigger:评论互动/蹭流量/Quote还是Repost/评论区抢占/comment engagement/quote vs repost/how to reply for exposure。不适用于:自己发原创帖(用x-short-content-craft)、冷启动整体策略排序(用x-cold-start-playbook)。

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用户要找对标账号/分析竞品爆款/找差异化选题时;或问"怎么做AI工具赛道的差异化""how to find benchmarks / differentiate"时。按5步走:找3-5个低粉高爆对标(搜索from:xxx min_faves:10)→分析90天爆款抓隐性需求→学互动策略→拆变现模式→三公式变形(场景细化/人群聚焦/观点反转)出差异。不适用于:已有定位日常发内容(→x-short-content-craft)、纠结选IP还是泛流量(→x-positioning-tradeoff)、检查草稿(→x-five-piece-checklist)、纯信息查询。

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when validate-chunk reports test failures specifically, when the user says "tests are failing", "figure out what's wrong with the tests", "fix the failing tests", or when test assertions don't match expected output after chunk implementation. Triages whether the test or the implementation is wrong and fixes the correct one.

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This skill should be used when the user says "lock it", "go with that", "approved", "that's the standard", or explicitly establishes a project-wide pattern like "from now on all forms should use this approach". Formalizes approved decisions into locked standards that the system enforces going forward. Not needed for story-scoped decisions — only for project-wide patterns.

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Enforcement layer for chunk and story validation. Invokes the chunk-validator agent (haiku), enforces the verdict, routes failures to refine-chunk or test-fix, captures CLI learnings. The orchestrator invokes this skill — never the agent directly.

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This skill should be used when validate-chunk reports errors or failures, when the user asks to "fix these errors", "resolve validation issues", "refine this chunk", or when specific build, lint, or type errors need surgical fixes. Makes precise, targeted edits to resolve specific validation issues without over-engineering.

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Interactive browser automation via playwright-cli. Use when you need to navigate a site, click elements, fill forms, take snapshots, or triage a live app.

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This skill should be used when the user asks to "plan chunks", "break this down", "plan the implementation", or when a story has status planning and needs implementation details before building. Required before any story can be implemented. Transforms story sparks into detailed chunk-by-chunk implementation plans with full technical specifics, file lists, and risk analysis. Supports parallel planning of multiple stories via batch mode.

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Use this skill when the user wants to discover, define, or refine their product's aesthetic identity. Triggers on "what should this feel like?", "help me figure out the vibe", "something feels off visually", "I want it to feel like [X]", "define the visual language", or when a project has no established design direction. This is the art director skill - it helps users articulate something they can feel but can't name. Also handles quick cohesion checks when the orchestrator needs one during cycle planning.

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This skill should be used when a story has been captured but content direction is unresolved - the spark describes WHAT to build structurally but not WHAT goes in it. Reads the story spark, splits it into Resolved (structurally clear) vs. Assumed (would have to guess) content dimensions, and surfaces each assumption for the human to confirm, correct, or expand. Also classifies implementation risk tags (has-variants, has-data-pipeline, has-animation, has-touch-targets, diverges-from-existing) so plan-chunks translates them into acceptance criteria that name the implementation mechanism. Captures answers into

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Executes a four-phase feature addition workflow (Discovery, Planning, TDD Implementation, Verification) for Python projects. Use when adding a new feature end-to-end — discovering project structure and integration points, drafting a feature spec with MoSCoW-prioritized requirements and BDD acceptance criteria, implementing via test-first TDD cycles, then verifying with ruff lint, ty type checks, and behavior-focused regression and contract coverage.

日本語の概要は準備中です。原文の説明を表示しています。