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World-class character and art style consistency for AI-generated images and videos - ensures visual coherence across series, maintains character identity, and provides rigorous QA before deliveryUse when "character consistency, art style, same character, consistent character, visual continuity, series, turnaround sheet, character sheet, reference image, character bible, style guide, anime character, consistent look, face consistency, outfit consistency, lora training, ip-adapter, flux kontext, visual qa, art quality, generation review, style drift, character drift, character-consistency, art-style, visual-qa, ai-art, image-generation, video-generation, anime, illustration, lora, ip-adapter, flux, midjourney, stable-diffusion" mentioned.

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。

软件架构 (含 应用架构 / 系统架构 / 分布式 后端架构 / 前后端 数据流 与 数据模型 设计 / API 边界 / 可扩展性 / 演进式架构 — 不含 硬件架构 / 纯企业架构 / 纯 DevOps / 纯安全架构) (software architecture — application & system architecture for web / mobile / distributed back-ends; designing services + data models + data flow + integration boundaries; making explicit trade-offs about scalability / coupling / consistency / evolvability; not hardware / chip architecture, not pure enterprise-architecture (TOGAF/Zachman), not pure DevOps / SRE, not pure security architecture (those are adjacent disciplines).) Master OS — automated mastery of software architecture — application & system architecture for web / mobile / distributed back-ends; designing services + data models + data flow + integration boundaries; making explicit trade-offs about scalability / coupling / consistency / evolvability; not hardware / chip architecture, not pure enterprise-architecture (TOGAF/Zachman), not pure DevOps / SRE, not pure security architecture (those are adjacent disciplines).: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on software architecture — application & system architecture for web / mobile / distributed back-ends; designing services + data models + data flow + integration boundaries; making explicit trade-offs about scalability / coupling / consistency / evolvability; not hardware / chip architecture, not pure enterprise-architecture (TOGAF/Zachman), not pure DevOps / SRE, not pure security architecture (those are adjacent disciplines). problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「软件架构」「系统设计」「system design」「应用架构」「service design」

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。

投行并购 (投行并购 / 交易撮合 (Investment Banking M&A / Dealmaking) — 面向并购顾问、企业融资、卖方/买方交易执行的职业认知操作系统，从业者(分析师 Analyst / 经理 Associate / 副总裁 VP / 董事 Director / 董事总经理 MD / 内部公司发展 Corp Dev / PE 投资人)、想入行者、以及服务这行(法律/会计/估值/咨询)的视角。覆盖: (a) 第一性张力 — 投行 M&A 的核心世界观分歧: **价格 vs 价值 (price 是市场愿意付的, value 是内在的, deal 在两者缝隙里成交) ⇄ 确定性 vs 最高价 (certainty of close 对卖方常胜过纸面最高报价) ⇄ 顾问/中介 vs 委托代理 (banker 是 agent, 客户利益 vs 成交费的激励冲突真实存在, 「banker 总想成交」是行业原罪批判)**; 更深层 — 「过程/竞价纪律 (controlled auction 制造竞争张力、信息不对称管理) ⇄ 关系/信任 (relationship banking、长期 coverage、reputational capital)」, 「叙事/包装 (the story, equity story, positioning) ⇄ 数字/尽调 (the numbers, diligence, quality of earnings)」, 「估值的科学外衣 (DCF/comps 的伪精确) ⇄ 谈判的真实定价 (价格由 leverage、竞争、时机决定)」; (b) 估值与分析正典 (最标准化、最易蒸出高质量+CLI 化) — DCF (折现现金流: FCF 预测/WACC 折现率/terminal value 终值/Gordon growth vs exit multiple), Comparable Companies (可比公司/trading comps: EV/EBITDA, EV/Revenue, P/E), Precedent Transactions (先例交易/deal comps: control premium 控制权溢价), LBO (杠杆收购模型: IRR/MOIC/debt schedule/sources & uses), Accretion/Dilution (增厚/摊薄分析: EPS 影响、pro forma), Sum-of-the-Parts (分部估值/SOTP), Football Field (估值区间图), Merger Model (合并模型: synergies 协同/purchase accounting/goodwill), Sensitivity/scenario; (c) 交易流程与产出物 — 卖方流程 (sell-side: teaser 简介 → NDA → CIM/IM 信息备忘录 → management presentation → IOI 意向函 → data room 数据室 → LOI/term sheet → confirmatory diligence → SPA 买卖协议 → signing → closing), 买方流程 (buy-side: thesis/sourcing → outreach → valuation → bid → exclusivity → diligence → financing → close), auction 类型 (broad/targeted/negotiated/preemptive bid); 产出物: pitchbook 推介材料、CIM、fairness opinion 公平意见、board presentation、fee letter、engagement letter; (d) 交易结构与条款 — consideration (cash/stock/mix/earnout 对赌)、deal protections (breakup fee 分手费/go-shop/no-shop/MAC 重大不利变化条款)、representations & warranties 陈述与保证、escrow 托管、working capital adjustment 营运资金调整、reverse termination fee、collar 价格区间、tender offer vs merger、hostile vs friendly、defensive tactics (poison pill 毒丸/white knight 白衣骑士/staggered board); (e) 行业结构与角色 — bulge bracket (高盛/摩根士丹利/JPM/BofA/花旗) vs elite boutique (Centerview/Evercore/Moelis/Lazard/PJT/Perella) vs middle market (Houlihan Lokey/William Blair/Harris Williams) vs regional/independent; analyst→associate→VP→director→MD 晋升金字塔; coverage (行业组) vs product (M&A/ECM/DCM/leveraged finance/restructuring); sponsors group (服务 PE); 买方包括 PE/strategic acquirer/corp dev; (f) 量化指标与节奏 — deal fee (success fee 业内通常约 1-2% 视规模递减/retainer/Lehman formula)、league table 排行榜、pitch→mandate 转化、deal velocity、hours culture (analyst 80-100h/week 文化批判)、bonus/comp 结构、deal sheet (简历上的成交清单); (g) 争议/批判 — fairness opinion 是否橡皮图章 (利益冲突: 出意见的 banker 也收成交费)、estimate 的伪精确 (DCF garbage in garbage out、假设驱动结论)、banker 永远建议成交 (deal 偏见、empire building 助推 CEO 自利并购)、协同效应系统性高估 (大量并购毁灭价值、winner's curse 赢家诅咒)、analyst 血汗工厂文化 (2021 高盛 13 人 deck 事件、过劳死争议)、advisory 价值 vs 中介寻租之争、bulge vs boutique 的利益独立性叙事 (boutique 标榜「无承销利益冲突」)、SPAC 泡沫与 de-SPAC 教训; (h) 流派/思想谱系 — 估值学派 (Aswath Damodaran 估值教父/纽大、Tim Koller McKinsey《Valuation》、McKinsey valuation 体系) vs 公司金融教科书派 (Rosenbaum & Pearl《Investment Banking》行业圣经、Brealey Myers Allen、CFI/WSP/BIWS 培训体系) vs 交易实战派 (Bruce Wasserstein《Big Deal》、Joseph Perella/Felix Rohatyn 老派 dealmaker、现代 boutique 创始人) vs 行为/批判派 (并购毁灭价值的学术证据、Damodaran 对协同/控制权溢价的批判、Matt Levine《Money Stuff》解构华尔街逻辑) vs PE/buy-side 视角 (LBO 数学、value creation 杠杆/运营/multiple expansion)。不含: 二级市场股票交易/卖方研究 (equity research)、零售财富管理/private banking、纯 ECM/IPO 承销执行 (虽相关但聚焦 M&A advisory)、纯 PE 投后运营、量化交易/对冲基金策略、纯公司财务报表会计。) Master OS — automated mastery of 投行并购 / 交易撮合 (Investment Banking M&A / Dealmaking) — 面向并购顾问、企业融资、卖方/买方交易执行的职业认知操作系统，从业者(分析师 Analyst / 经理 Associate / 副总裁 VP / 董事 Director / 董事总经理 MD / 内部公司发展 Corp Dev / PE 投资人)、想入行者、以及服务这行(法律/会计/估值/咨询)的视角。覆盖: (a) 第一性张力 — 投行 M&A 的核心世界观分歧: **价格 vs 价值 (price 是市场愿意付的, value 是内在的, deal 在两者缝隙里成交) ⇄ 确定性 vs 最高价 (certainty of close 对卖方常胜过纸面最高报价) ⇄ 顾问/中介 vs 委托代理 (banker 是 agent, 客户利益 vs 成交费的激励冲突真实存在, 「banker 总想成交」是行业原罪批判)**; 更深层 — 「过程/竞价纪律 (controlled auction 制造竞争张力、信息不对称管理) ⇄ 关系/信任 (rela

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。

亚马逊管理之道 (亚马逊管理之道 (The Amazon Way — Amazon 自身的领导力与运营操作系统) — 这个 master skill 蒸馏的不是『在亚马逊平台上开店卖货』(那是跨境电商运营,已由 cross-border-ecommerce 另蒸),也不是 AWS 云技术架构;而是亚马逊这家公司『怎么运营自己、怎么做决策、怎么招人、怎么创新、怎么规划』的一整套可迁移的管理机制(mechanisms)与心智操作系统。面向想在自己团队/公司引入亚马逊式机制的创始人/CEO/高管/运营负责人(COO)、产品经理与技术产品经理(PM/PMT)、组织与流程设计者(chief of staff / ops)、以及在亚马逊工作或准备面试亚马逊(著名的 LP 行为面试 + Bar Raiser)的人。覆盖: (a) 第一性张力 — 亚马逊 OS 的核心世界观分歧: **机制 > 良好意图(Good intentions don't work, mechanisms do:问题不能靠『下次更努力』修复,要装一个带检查闭环的自我强化流程) ⇄ 可控输入指标 vs 滞后输出指标(管你能控制的 input 如选品/价格/在库/配送速度,而非 revenue/股价这类滞后又不可控的 output) ⇄ 长期主义 vs 季度业绩(Day 1、willing to be misunderstood、用现金流+飞轮长期投入,宁可牺牲短期利润) ⇄ 客户执念 vs 竞争对手执念(working backwards 从客户倒推,而非从竞品或『我们能造什么』正推) ⇄ 叙事备忘录 vs PPT(6-pager + 开会前静默阅读、动手前先写 PR/FAQ;写作逼出清晰思考,禁 PowerPoint) ⇄ 单线程负责人/两个披萨团队 vs 协调税(separable、autonomous、one owner per initiative,砍掉跨团队依赖) ⇄ 高标准可学习可传递 vs 与生俱来(insist on the highest standards + Bar Raiser 招聘门,标准是 domain-specific 且能教的) ⇄ 节俭催生创造力 vs 血汗文化(frugality/约束驱动发明 —— 但 frugality + 高压 bar + URA 强制淘汰 = 文化阴暗面批判) ⇄ 两类决策(Type 1 不可逆/单向门 慎重 vs Type 2 可逆/双向门 高判断力个人快速决策,别用重流程拖慢))**; (b) 核心机制(mechanisms,本行的『工具栈』其实是一套运营机制而非软件) — Leadership Principles(14 条→2021 增至 16 条,是一套运营语言和决策仲裁器)、Working Backwards(从客户倒推:动手前先写新闻稿+常见问答 PR/FAQ)、叙事备忘录(6-pager narrative / 1-pager + silent reading 静默阅读、禁 PPT)、Weekly Business Review(WBR + metrics deck 指标看板)、input/output metrics(可控输入指标体系、DMAIC 式指标选择)、年度规划(OP1/OP2 + S-Team goals)、Bar Raiser(招聘机制,独立于用人经理的抬杠者拥有一票否决)、Two-Pizza Team / Single-Threaded Leader STL / separable teams、Correction of Errors(COE 事故复盘 + 5 Whys 五问法)、Andon Cord(安灯绳,借自丰田,一线可拉停)、Flywheel(飞轮:低价→更多客户→更多卖家→更多选品→更低成本结构→更低价)、Type 1/Type 2(单向门/双向门决策分级)、Regret Minimization Framework(遗憾最小化,贝索斯创业决策法); (c) 心智模型层 — customer obsession(客户执念是所有 LP 之首)、long-term thinking / Day 1(第二天就是停滞衰亡)、invent and simplify、ownership(主人翁,不说 that's not my job)、bias for action(可逆决策就快,speed matters)、disagree and commit(充分反对后即便不同意也全力执行)、frugality、dive deep(深入细节、不靠代理指标脱离一线)、think big、are right a lot(用强判断力和证伪自己的能力多做对的判断)、earn trust、deliver results; (d) 工作流/SOP — 用亚马逊方式发起一个新产品/业务(先写 PR/FAQ→评审→倒推着造)、如何跑一场 WBR、如何写和评审一份 6-pager(叙事流程 + 静默阅读)、Bar Raiser 招聘 loop、年度规划(OP1/OP2→S-Team goals→输入指标追踪)、事故后的 Correction of Errors; (e) 知识正典(en-primary,极其丰富且可取一手) — 贝索斯致股东信 1997-2021(1997 首封是奠基文本,每年附在信末;Day 1、遗憾最小化、long term)、《Working Backwards》Colin Bryar & Bill Carr(2021,运营机制圣经)、《The Everything Store》Brad Stone(2013,公司史)、《Amazon Unbound》Brad Stone(2021,权力与阴暗面续作)、《Invent and Wander》贝索斯文集(2020)、《The Amazon Way》/《Think Like Amazon》John Rossman(前亚马逊高管)、Amazon 官方 Leadership Principles 页(amazon.jobs,一手)、HBR『The Institutional Yes』(2007 贝索斯访谈); (f) 行业大佬/figures — Jeff Bezos(创始人,源头教义)、Andy Jassy(现任 CEO,OS 超越创始人的证据 + AWS 缔造者)、Colin Bryar(前贝索斯影子/TPM,《Working Backwards》作者)、Bill Carr(前数字媒体 VP,《Working Backwards》作者)、Jeff Wilke(前全球消费者 CEO,运营架构师)、John Rossman(前亚马逊、机制布道者/顾问)、Brad Stone(记者/编年史作者,批判性外部视角); (g) 争议/批判(必须保留,不能洗白) — 文化阴暗面(NYT 2015『Inside Amazon: Wrestling Big Ideas in a Bruising Workplace』揭露高压职场)、仓储与一线劳工争议、URA(unregretted attrition 强制淘汰)与 stack-ranking 的残酷、frugality + 高 bar = 燃尽(burnout);机制能否迁出亚马逊(cargo-culting:在初创或非科技公司照搬 PR/FAQ/输入指标/Bar Raiser 常失败);是贝索斯个人天才(personality)还是制度化机制(institution)—— OS 在贝索斯卸任后于 Jassy 治下延续,是机制派的证据; (h) 流派/思想谱系 — **信徒/机制布道派(Bryar & Carr《Working Backwards》+ 前亚马逊 operator 顾问圈,信 mechanisms 可移植、任何公司可安装)** vs **批判派(Brad Stone《Amazon Unbound》+ NYT + 劳工视角,认为 OS 与高淘汰的残酷机器不可分割,不该被浪漫化)** vs **情境/规模怀疑派(机制之所以有效是因为亚马逊特定的规模/现金流/创始人权力,照搬到小公司=cargo cult)** vs **创始人中心 vs 制度中心之争(是贝索斯个人 vs 可传承的机制)**。不含: 在亚马逊开店卖货/选品/PPC/FBA 的卖家运营(=cross-border-ecommerce)、AWS 云技术架构与运维、通用 MBA 管理理论泛泛而谈、把普通商业常识包装成『亚马逊独家秘诀』。) Master OS — automated mastery of 亚马逊管理之道 (The Amazon Way — Amazon 自身的领导力与运营操作系统) — 这个 master skill 蒸馏的不是『在亚马逊平台上开店卖货』(那是跨境电商运营,已由 cross-border-ecommerce 另蒸),也不是 AWS 云技术架构;而是亚马逊这家公司『怎么运营自己、怎么做决策、怎么招人、怎么创新、怎么规划』的一整套可迁移的管理机制(mechanisms)与心智操作系统。面向想在自己团队/公司引入亚马逊式机制的创始人/CEO/高管/运营负责人(COO)、产品经理与技术产品经理(PM/PMT)、组织与流程设计者(chief of staff / ops)、以及在亚马逊工作或准备面试亚马逊(著名的 LP 行为面试 + Bar Raiser)的人。覆盖: (a) 第一性张力 — 亚马逊 OS 的核心世界观分歧: **机制 >

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。

AI citation readiness audit ONLY (does not touch Google rankings, use blog-rewrite for combined Google+AI work). Use whenever the user wants their content to rank in ChatGPT, Perplexity, Claude, Gemini, or Google AI Overviews. AI citation optimization audit scoring blog posts for ChatGPT, Perplexity, and Google AI Overview citability. Evaluates passage-level citability, Q&A formatting, entity clarity, structured data, and AI crawler accessibility. Generates citation capsules and a 0-100 AI Citation Readiness score. Use when user says "geo", "ai citation", "ai optimization", "citation audit", "aeo", "perplexity optimization", "chatgpt citation".

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。

Use the corp-finance-mcp server tools for specialty finance, regulatory, and compliance calculations. Invoke when performing private credit (unitranche, direct lending, syndication), insurance (loss reserving, premium pricing, Solvency II SCR), FP&A (variance analysis, break-even, working capital, rolling forecast), wealth management (retirement planning, tax-loss harvesting, estate planning), restructuring (recovery analysis, distressed debt), real assets (property valuation, project finance), venture capital (dilution, convertible instruments, fund returns), ESG (scoring, climate/carbon, green bonds, SLL), regulatory capital (Basel III, LCR/NSFR, ALM), compliance (MiFID II best execution, GIPS reporting), credit derivatives (CDS pricing, CVA/DVA), convertible bonds (binomial tree pricing, scenario analysis), lease accounting (ASC 842/IFRS 16, sale-leaseback), pension & LDI (funding analysis, liability-driven investing), sovereign risk (bond analysis, country risk), real options (binomial valuation, decision trees), equity research (SOTP, target price), commodity trading (spread analysis, storage economics), treasury management (cash management, hedge effectiveness), infrastructure finance (PPP models, concession valuation), crypto (token valuation, DeFi analysis), municipal bonds (pricing, credit analysis), structured products (notes, exotic), trade finance (LC, supply chain), fund structuring (US onshore, UK/EU, Cayman/BVI offshore, Luxembourg/Ireland), transfer pricing (BEPS/Pillar Two, intercompany pricing), tax treaty (treaty network optimization, holding structures), FATCA/CRS (reporting, entity classification), economic substance (multi-jurisdiction testing), regulatory reporting (AIFMD Annex IV, SEC Form PF, CFTC CPO-PQR), AML compliance (KYC risk scoring, sanctions screening), fund of funds (J-curve, commitment pacing, manager selection, secondaries pricing), bank analytics (NIM analysis, CAMELS rating, CECL provisioning, deposit beta, loan book), carbon markets (credit pricing, ETS compliance, CBAM, offset valuation, shadow carbon price), private wealth (concentrated stock, philanthropic vehicles, wealth transfer, direct indexing, family governance). All computation uses 128-bit decimal precision.

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。

Use when identifying cybersecurity-specific regulations and incident reporting obligations. Covers NIS2, DORA, SEC cyber disclosure rules, CISA incident reporting, state breach notification laws, cyber insurance requirements, and security certification frameworks. USE FOR: NIS2, DORA, SEC cybersecurity rules, CISA, breach notification, incident reporting, SOC 2, ISO 27001, cyber insurance, FedRAMP, StateRAMP, CMMC, data breach response DO NOT USE FOR: implementing security controls (use security skills), security testing tools (use security/security-testing), general data privacy (use privacy-data-protection)

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。

Auto-selects and enforces the strongest valid Python typing lane for the detected Python version and dependencies — no user input required. Use when adding or tightening type annotations, eliminating Any usage in internal code, designing boundary validators or parsers, choosing between stdlib typing (TypedDict, Protocol, dataclasses), Pydantic models, or Hypothesis property tests, addressing ty or mypy failures, or applying version-specific features (TypeIs, ReadOnly, PEP 695 generics, PEP 649 deferred evaluation). Enforces boundary isolation — raw payloads validated immediately at ingress and returned as typed internal objects.

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。

Comprehensive SEO analysis for any website or business type. Performs full site audits, single-page deep analysis, technical SEO checks (crawlability, indexability, Core Web Vitals with INP), schema markup detection/validation/generation, content quality assessment (E-E-A-T framework per Dec 2025 update extending to all competitive queries), image optimization, sitemap analysis, and Generative Engine Optimization (GEO) for AI Overviews, ChatGPT, and Perplexity citations. Analyzes AI crawler accessibility (GPTBot, ClaudeBot, PerplexityBot), llms.txt compliance, brand mention signals, and passage-level citability. Industry detection for SaaS, e-commerce, local business, publishers, agencies. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "page speed", "structured data".

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。

Analyze a tensegrity system by identifying compression struts and tension cables, classifying type (class 1/2, biological/architectural), computing prestress equilibrium, verifying stability via Maxwell's rigidity criterion, and mapping biological tensegrity (microtubules, actin, intermediate filaments). Use when evaluating tensegrity in architecture, robotics, cell biology, or any system with isolated compression in continuous tension.

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Entity Framework Core patterns for ASP.NET Core projects: DbContext design, code-first entity configuration (Fluent API via IEntityTypeConfiguration<T>), relations (HasOne/HasMany, cascade/restrict/set-null), indexes and unique constraints, projection to DTOs (Select + AsNoTracking), avoiding N+1 (Include, AsSplitQuery), transactions, parameterized raw SQL (FromSql with FormattableString), and connection string from IConfiguration. Works alongside aspnet-core-plugin:aspnet-conventions. Use this skill to: - Design a clean DbContext with ApplyConfigurationsFromAssembly for scalable entity registration. - Configure entity properties (column types, max length, precision, nullability) via Fluent API. - Avoid N+1 query problems with explicit Include / projection to DTOs. - Use transactions correctly for multi-entity operations. - Write parameterized raw SQL safely when LINQ is not expressive enough. Do NOT use this skill for: - Migration generation commands (that is efcore-specialist's job in the database extra phase). - ASP.NET Core middleware, DI, or validation — see aspnet-core-plugin:aspnet-conventions. - C# language idioms — see csharp-foundation:csharp-conventions.

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Modern PHP idioms for any PHP project (PHP 8.1+): readonly properties, enums, match expressions, constructor property promotion, typed properties, named arguments, nullsafe operator, first-class callable syntax, strict_types, PSR-12 style, and null discipline. Apply when the project is a PHP 8.1+ project. Stack-agnostic — referenced by every PHP plugin in the marketplace. Use this skill to: - Write strongly-typed, immutable-by-default value objects with readonly properties and enums. - Replace switch ladders and magic constants with match expressions and backed enums. - Cut constructor boilerplate with property promotion and express optionality with typed nullable returns. - Keep code PSR-12 compliant with declare(strict_types=1) in every file. Do NOT use this skill for: - Framework-specific idioms (Eloquent, Doctrine, Symfony services, Laravel facades — those live in framework plugin skills). - Composer / autoloading / dependency management — see php-foundation:composer-tooling. - Testing patterns — see php-foundation:php-testing.

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Write a vulnerability report. Use when the user says "vulnerability report", "vuln report", "security finding", "write up this finding", "pentest finding", "bug bounty report", "security disclosure", "CVE writeup", "document this vulnerability", "how to report a security issue", or needs to formally document a security vulnerability with evidence, impact, and remediation guidance - even if they don't explicitly say "report".

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Use when picklist data quality has degraded: unrestricted picklists accepting garbage API values, dependent picklist relationships bypassed by integrations, record type picklist value mappings drifting out of sync, or orphaned values appearing in reports. NOT for the value-deactivation runbook or the API-name-vs-label trap — use admin/picklist-data-integrity. NOT for initial picklist creation or Global Value Set design — use admin/picklist-and-value-sets. NOT for record type configuration itself — use admin/record-types-and-page-layouts.

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Custom Notification Types for desktop/mobile push alerts from Flow or Apex: type creation, target channels, Messaging.CustomNotification invocation, recipient limits, bulk notification patterns. NOT for choosing channels, consent, or notification-fatigue policy — use admin/custom-notification-type-design. NOT for email alerts — use admin/email-templates-and-alerts. Trigger keywords: notiftype, notificationtypes directory, customNotifTypeName, customNotificationAction, setNotificationTypeId, targetPageRef, NotificationTypeConfig.

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Design the engagement model for an Experience Cloud community: reputation levels, ideation, and content contribution strategy. Triggers: 'community engagement strategy', 'gamification Experience Cloud', 'reputation levels setup', 'ideation community portal', 'member recognition program'. NOT for blocking, flagging or approving what members post — use admin/experience-cloud-moderation. NOT for measuring logins, page views or engagement after launch — use data/community-analytics-data. Also covers: the Network reputation elements that carry the ladder (enableReputation, reputationLevels/level/label/lowerThreshold, reputationPointsRules/pointsRule/eventType/points), the 16 documented reputation eventType values and their default points, ManagedTopics / ManagedTopic (Navigational vs Featured, position 0-24), NetworkMember.ReputationPoints seeding, and why FeedItem cannot carry the engagement dashboard.

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Task and Event objects: polymorphic WhatId/WhoId, Activity object model, ActivityHistory vs OpenActivity, activity timeline customization, bulk task creation, Einstein Activity Capture boundaries. NOT for turning on EAC or calendar sync — use admin/einstein-activity-capture-setup. NOT for Email-to-Case — use admin/case-management-setup. Covers ActivitiesSettings metadata, enableActivities, shared Task/Event custom fields and FLS, TaskStatus value sets, Shared Activities and TaskRelation/EventRelation, recurring and child activities, and partial-success bulk DML on Task.

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Create and configure Lightning apps in Salesforce Setup, add navigation items and tabs to apps, configure utility bar components, and control app visibility by profile or permission set. Also covers the deployable metadata behind all of that: CustomApplication, CustomTab, and the FlexiPage of type UtilityBar. Trigger keywords: Lightning app, App Manager, custom tab, navigation bar, utility bar, app visibility, CustomApplication, tabs element, standard- tab prefix, defaultLandingTab, formFactors, navType, uiType, workspaceConfig, applicationVisibilities, tabSettings, AppDefinition, TabDefinition, AppTabMember, app deployed but not visible. NOT for console navigation, workspace tabs and subtabs - use admin/service-console-configuration. NOT for the record page or app page inside the app - use admin/lightning-app-builder-advanced.

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Author and own ONE content type's typed schema (the CONTENT-TYPE.md) at .unikit/gamedesign/content-types/CT-<slug>.md — the content / catalog layer of the GDD (cards, items, weapons, enemies, levels, quests, loot). Use whenever the user wants to ADD a new kind of content or UPDATE its schema, e.g. "add a new content type", "design the loot content", "define the card schema", "add an enemies content type", "add a rarity field to items", "switch this catalog to curated". Create the skeleton, fill its typed field schema (CT.fields), scale, relationships, and validation, AND revise the schema under the delta discipline (a schema change bumps the version + changelog). Selects the scale (bulk | curated) and self-registers content_types/content. This owns the content SCHEMA, not the catalog of values — adding individual entries/units is data handled in the editor, not a schema edit. To add or detail a system use /unikit-gd-system; to add a flow use /unikit-gd-flow; to apply a multi-zone edit use /unikit-gd-apply.

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Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-analysis).

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Synthesized reference notes from three US Government vehicle-safety sources: NHTSA Cybersecurity Best Practices for the Safety of Modern Vehicles (updated 2022, final), NHTSA Automated Driving Systems 2.0: A Vision for Safety (2017), and a 16-section selection of 49 CFR Part 571 (FMVSS) pinned at eCFR versioner date 2025-01-01. Use for voluntary vehicle cybersecurity practices, the ADS 2.0 twelve priority safety design elements, and FMVSS occupant protection, brakes/stability/lighting, and fuel/EV integrity requirements. Not ISO 26262, not ASPICE, not ISO/SAE 21434, not UNECE R155/R156, not SAE J3016, and not the full Part 571; the FMVSS material is a selection of vehicle-level minimum performance standards, not a process standard.

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Knowledge base from NASA System Safety Handbook Volume 2 (NASA/SP-2014-612). Use for risk-informed safety cases (RISC), integrated safety analysis (ISA), adequate safety concepts, safety objectives and requirements, acquirer/provider roles, graded safety analysis, claims-evidence-argument structure, SSMP development, and RISC evaluation. Does not cover nuclear or chemical safety domains, occupational health regulations, or NASA-specific programmatic requirements beyond system safety.

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Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental design.

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Apply a scholarly 'nerd' visual style to single-file handwritten HTML document sites: publication-list look, restrained typography, no frameworks. Use when building or reviewing a lab site, a publications page or any new page that should match this house style. Triggers: /scholar-nerd-style, /nerd, nerd style, scholar style, build a page in our style, check page style.

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