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Retrieve translated patent description (specification) text from Nexscope. Triggered when users request patent specification translation, patent full text in other languages, translated patent full text, or want to view patent specifications in Chinese, English, or Japanese, patent specification translation, patent description translation, Nexscope, or patent translation. Also triggered when users provide a patent ID or publication number and request specification/description content in another language, or mention "patent specification translation," "description translation," "translated full text," or similar intent.

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Win #1 Product of the Day on Product Hunt. Completely reverse-engineered from 30x daily winner and 3x weekly winner campaigns — ranking algorithm decoded, launch timing optimized, hunter selection guide, community engagement approach, and post-launch momentum playbook. Use this if you're: (1) already read PH launch guides but still can't break into Top 5 and need algorithm-level deep optimization, (2) targeting Daily #1 and 5,000+ sign-ups with a proven 30+ case validated approach, or (3) an investor/accelerator coaching portfolio companies on PH launches. What's inside: PH ranking algorithm decoded: weighted factors for first 3 hours, 24 hours, and weekly ranking · Pre-launch preparation: gallery optimization, product URL selection, tagline refinement (≤60 chars) · Launch timing optimization: exact PST launch windows + scheduling guide · Community engagement KPIs: upvote targets, comment response time, maker comment strategy · Platform compliance guide: understanding PH's quality signals and organic growth · Post-launch 72-hour plan: maintaining momentum, conditions for Weekly #1 · Case studies: 3 different categories (AI Tool, App, SaaS) dissected Expected outcomes: Product Hunt Daily #1 ranking · strong community engagement on launch day · 3,000–10,000+ sign-ups (depending on product-market fit) 🇨🇳 Product Hunt 打榜完整攻略 | 🇯🇵 Product Hunt ローンチガイド | 🇰🇷 Product Hunt 런칭 가이드 Keywords: Product Hunt #1, Product Hunt launch strategy, PH ranking algorithm, PH #1 daily winner, Product Hunt tips, product launch, startup launch, ranking optimization, PH gallery optimization, Community engagement strategy, maker community engagement, product strategy, launch tactics, how to win Product Hunt, product hunt best practices

🇺🇸 SEO & GEO Dual-Engine Playbook 2026 — Rank on Google AND get cited by AI search (ChatGPT, Perplexity, Claude, Gemini). Battle-tested from AFFiNE (60k GitHub stars in 24 months) and 150+ AI startup consultations. E-E-A-T writing voice system, keyword funnel strategy, JSON-LD schema templates, comparison page SOP, IndexNow setup, Generative Engine Optimization content patterns. **Optimized for dev tools / OSS / B2B SaaS. 2C products (education, apps, games): see 2c-adaptation guide in references/.** 🇨🇳 SEO & GEO 双引擎增长手册 —— 同时拿下 Google 排名和 AI 搜索引用（ChatGPT、Perplexity、Claude、文心一言）的完整方法论。AFFiNE 60k stars 与 150+ AI 创业公司咨询实战验证。E-E-A-T 写作声音系统、关键词漏斗、JSON-LD 结构化数据、竞品对比页 SOP、IndexNow 推送、生成式引擎优化内容模式。**默认适用于开发者工具 / 开源项目 / B2B SaaS，2C 产品（教育/应用/游戏）请参考 references/2c-adaptation.md。** 🇯🇵 SEO & GEO デュアルエンジングロースプレイブック — Google検索とAI検索（ChatGPT、Perplexity、Claude）の両方で評価される手法。AFFiNE 60k starsと150社以上のAIスタートアップコンサルティングで検証。E-E-A-Tライティング、キーワードファネル、Schema.org構造化データ、比較ページSOP。**デフォルトは開発者ツール／OSS／B2B SaaS向け。2C製品（教育・アプリ・ゲーム）はreferences/2c-adaptation.mdを参照。** 🇰🇷 SEO & GEO 듀얼 엔진 성장 플레이북 — 구글 검색과 AI 검색(ChatGPT, Perplexity, Claude) 양쪽 모두에서 인용되는 방법론. AFFiNE 60k 스타와 150+ AI 스타트업 컨설팅으로 검증. E-E-A-T 글쓰기, 키워드 퍼널, Schema.org 구조화 데이터, 비교 페이지 SOP. **기본값은 개발자 도구/OSS/B2B SaaS용. 2C 제품(교육·앱·게임)은 references/2c-adaptation.md 참조.** Triggers: "SEO" | "GEO" | "Generative Engine Optimization" | "AI search optimization" | "ChatGPT SEO" | "Perplexity SEO" | "Claude SEO" | "search optimization" | "content SEO" | "technical SEO" | "schema markup" | "JSON-LD" | "structured data" | "IndexNow" | "E-E-A-T" | "keyword strategy" | "keyword funnel" | "comparison page" | "programmatic SEO" | "SaaS SEO" | "搜索优化" | "AI 搜索" | "内容 SEO" | "GEO 优化" | "生成式引擎优化"

You launched an ambassador program. 3 applications. One ghosted after week 2. Should you lower the bar? Offer more perks? Spam influencers? This gives you the community & ambassador operations SOP with volunteer, paid tutorial creator and code-contributor tracks — from pre-launch checklist to recruitment to tiered management to retention to governance. Built from Notion (20M users, real ambassador interviews), AFFiNE (60K stars), Asana, and ClickUp programs. By @WeiYipei. 🇨🇳 你搞了个大使计划。来了3个申请。一个第二周就消失了。该降门槛？加福利？群发KOL？这份SOP给你从启动前置条件到招募到留存到治理的完整社区/大使运营方法论。基于 Notion（2000万用户，大使真实访谈）、AFFiNE（60K stars）、Asana、ClickUp 实战案例。 🇯🇵 アンバサダープログラムを立ち上げた。応募3件。1人は2週間で消えた。基準を下げる？特典を増やす？このSOPは、事前チェックリストから採用、段階管理、リテンション、ガバナンスまでの完全なコミュニティ＆アンバサダー運営フレームワークを提供します。Notion（2000万ユーザー）、AFFiNE（60K stars）の実例から構築。 🇰🇷 앰배서더 프로그램을 시작했습니다. 지원 3건. 하나는 2주 만에 사라졌습니다. 기준을 낮출까요? 이 SOP는 사전 체크리스트부터 모집, 단계별 관리, 리텐션, 거버넌스까지 완전한 커뮤니티 & 앰배서더 운영 프레임워크를 제공합니다. Notion(2000만 사용자), AFFiNE(60K stars) 실전 사례에서 구축. Triggers: "ambassador program" | "community building" | "community management" | "DevRel" | "developer relations" | "community growth" | "大使计划" | "社区运营" | "社区搭建" | "コミュニティ運営" | "アンバサダー" | "커뮤니티 운영" | "앰배서더" | "open source community" | "user retention"

Your competitor just launched. You have no idea how they grew so fast. Should you reverse-engineer their website? Track their social media? Map their growth flywheel? This gives you the complete SOP — from Wayback Machine snapshots to X/Twitter propagation analysis to growth flywheel scoring. Built from 150+ AI startup competitive analyses including the Lovable case study (4.3M views, 229K impressions launch day). By @WeiYipei. What's inside: • 4-step research framework (website teardown → social media → traffic sources → ad spend) • 3-version website evolution analysis (V1 / Beta / Launch via Wayback Machine) • X/Twitter propagation chain mapping (4-phase model + single-post teardown template) • Growth flywheel 6-stage scoring system (Activation → Referral → Acquisition → Retention → Revenue → Product) • KOL identification framework (Traffic King / Topic Starter / Mindset Shifter) • Content effectiveness ranking (validated: Visual Demo > User Story > Competitor Comparison) • ICP deep analysis template + Freemium pricing teardown • Complete self-check checklist 🇨🇳 你的竞品刚刚爆了。你完全不知道他们怎么做到的。该拆官网？盯社媒？画增长飞轮？这份 SOP 给你从 Wayback Machine 快照到 X/Twitter 传播链路还原到飞轮六阶段评分的完整方法论。基于 150+ AI 创业公司竞品分析实战，含 Lovable 完整案例。 🇯🇵 競合が突然バズった。どうやって成長したか全く分からない。このSOPは、Waybackスナップショットからツイッター伝播チェーン分析、フライホイール6段階スコアリングまでの完全な競合調査フレームワークを提供します。150以上のAIスタートアップ分析から構築。 🇰🇷 경쟁사가 갑자기 폭발적으로 성장했습니다. 어떻게 그렇게 빨리 성장했는지 모릅니다. 이 SOP는 Wayback 스냅샷부터 X/Twitter 전파 체인 분석, 플라이휠 6단계 스코어링까지 완전한 경쟁사 조사 프레임워크를 제공합니다. 150개 이상의 AI 스타트업 분석에서 구축. Triggers: "competitor research" | "competitive analysis" | "competitor analysis" | "growth flywheel" | "market research" | "竞品调研" | "竞品分析" | "增长飞轮" | "传播链路" | "競合分析" | "경쟁사 분석" | "social media teardown" | "Twitter propagation" | "content strategy analysis"

This skill should be used when the user asks to create custom Remotion transitions, asks about "cool transitions", "cinematic transitions", "striped transitions", "glitch transitions", "custom TransitionPresentation", or wants to build scene-to-scene transitions in Remotion beyond the built-in library. Also triggers for "how to make transitions in Remotion", "custom transition", "high-energy transitions", "energy transitions", "branded transitions".

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Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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。

Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

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。

TypeScriptのバックエンドでPrismaを使う際の設計・実装を支援します。検索や一括更新、移行、接続管理のパターンと注意点を具体例で確認できます。

• Prismaのモデルと関連を設計したいとき
• 検索処理とページ分割の見直し
• トランザクションや一括更新の不具合調査

React / Next.jsのボタン、モーダル、通知、ページ遷移に動きを加え、表示・消去やスクロールに連動するアニメーションを実装するスキル。

• ボタンの操作に動きを付けたいとき
• モーダルや通知の表示・消去
• Next.js App Routerのページ遷移

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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Designs QTL colocalization studies that connect eQTL, pQTL, sQTL, or related molecular QTL signals with GWAS loci. Always use this skill whenever a user wants to plan, scope, or structure a locus-level study asking whether a GWAS association and a molecular QTL association may reflect the same underlying causal signal. Covers locus definition, QTL/GWAS source architecture, ancestry and LD alignment, single-locus vs multi-locus strategy, candidate-gene prioritization, optional fine-mapping, linked MR/SMR follow-up, and functional annotation. Always output four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, evidence hierarchy, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references. Never equate colocalization with causality proof, mediation proof, or automatic target validation. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets, repositories, consortia, or public resources.

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Generates complete comorbidity-oriented shared-biomarker bioinformatics research designs from a user-provided disease pair and validation direction. Use when a study links two clinically related diseases through shared DEGs, enrichment, PPI hub genes, machine-learning feature selection, public diagnostic validation, gene-regulatory networks, immune infiltration, and optional downstream follow-up. Covers five study patterns (shared-DEG discovery, hub-gene prioritization, machine-learning biomarker selection, immune/regulatory interpretation, multi-layer validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

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Generates complete cross-disease shared-biomarker bioinformatics research designs from a user-provided disease pair and validation direction. Always use this skill whenever a user wants to design, plan, or build a multi-dataset study linking two related diseases through shared DEGs, enrichment, PPI hub genes, public validation, regulatory-network analysis, immune infiltration, drug-gene interaction screening, and optional qRT-PCR or cell-line validation. Covers five study patterns (shared-DEG discovery, hub-gene prioritization, regulatory-network interpretation, immune/drug follow-up, bioinformatics-plus-validation) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and a strictly verified reference literature retrieval layer with real references only.

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Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. **Trigger when user asks to:** - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration **Prerequisites:** Tables already identified as candidates (use find-hypertable-candidates first if needed) **Keywords:** migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries.

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Market positioning strategy using the April Dunford framework, enriched with JTBD discovery, Moore positioning statement, and Neumeier's Onliness Test. Produces a complete positioning document, positioning statement, competitive alternatives map, and market category analysis. Use when the user wants to define or refine their market positioning, find their unique position, differentiate from competitors, craft a positioning statement, choose a market category, or figure out "how should we position this product." Triggers for "positioning", "how to position", "market position", "differentiation strategy", "positioning statement", "competitive positioning", "category strategy", "where do we fit in the market", "how are we different", "unique value proposition", or any request to define, sharpen, or rethink positioning. Works standalone — no prior startup-design or startup-competitors session needed, but leverages their output if available.

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EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-session.

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Conducts Data Protection Impact Assessments for biometric identification and authentication systems under GDPR Article 35 and Article 9 special category rules. Covers facial recognition, fingerprint, iris scanning, voice recognition, and behavioural biometrics. Applies EDPB Guidelines 3/2019, CNIL Reglement Type Biometrie, and ISO/IEC 24745 biometric template protection. Keywords: DPIA biometric, facial recognition, fingerprint, Art. 35, Art. 9, biometric template, special category.

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Manages coordinated breach notification across multiple legal jurisdictions including EU member states (72-hour GDPR deadline), US state breach notification laws (varying timelines from 30 to 90 days), and other international regimes. Covers conflict resolution when notification timelines differ, lead supervisory authority determination, and parallel notification execution. Keywords: multi-jurisdiction, cross-border breach, notification coordination, GDPR, US state laws, international breach notification.

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Batch effect correction for CRISPR screens covering ComBat empirical-Bayes, RUV, SVA, control-sgRNA normalization, and the model-based alternative of including batch as a covariate in MAGeCK MLE or Chronos. Covers screen-specific batch sources (passage cohort, library lot, infection day, sequencing run, Cas9 lot, FBS lot), PCA + variance-decomposition diagnostic to decide if correction is needed, when correction harms biology by over-correcting condition into batch, limma removeBatchEffect for visualization-only correction, and relationship to multi-condition design matrices. Use when combining screens for joint analysis, when passage cohort confounds biology, when DepMap-style panels need Chronos with batch covariates, when picking ComBat vs RUV, or when correction harms biology and should be replaced with explicit covariate modeling.

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。

影视编剧 (Scriptwriting / Screenwriting) — 为电影 / 电视 / 流媒体剧集写戏剧蓝本的从业者认知操作系统: 决定「讲什么故事、人物是谁为何转变、场景如何被戏剧化、主题为何重要」的学科 —— 区别于导演 (调度 / 视觉实现)、制片 (融资 / 排期)、小说 (无格式 / 场景 / 视觉动作约束)。覆盖 (a) 故事与结构理论 (亚里士多德《诗学》情节 / 人物 / 思想 + 突转 peripeteia / 发现 anagnorisis + 净化 catharsis; Syd Field 范式 / 三幕 / 情节点; Freytag 金字塔; Egri 前提; McKee《故事》掌控性理念 / 鸿沟 / 价值正负转变 / 激励事件 / 渐进式复杂化; Truby《故事剖析》22 步 + 道德论证; Vogler/Campbell 英雄之旅; Blake Snyder《救猫咪》15 拍节拍表; Dan Harmon 故事环; John Yorke 五幕《进入森林》; Frank Daniel 八序列法; 起承转合东亚戏剧结构), (b) 人物 (想要 vs 需要 / 外在目标 vs 内在缺失, 人物弧光 正 / 负 / 平, flaw-wound-ghost 创伤背景, 主动 vs 被动主角的能动性, Egri 三维人物 生理 / 社会 / 心理, 反派是主角的镜子, 群像与关系网, 人物在压力下的选择中显形), (c) 对白 (潜台词 subtext, 对白即动作与冲突而非信息, 避免太直白 on the nose, 人物独特声口, 信息植入 exposition, Mamet/Sorkin 意图-阻碍式对白, 展示而非告知, 中文剧台词工艺), (d) 场景与序列工艺 (场景是有目标 / 冲突 / 转折的微型故事, 场景价值充能与转折点, 晚进早出, 八序列法, set piece, 转场, 场景头 / 动作行 / 括号提示 格式工艺), (e) 主题与前提 (掌控性理念 / 前提, 主题是被戏剧化的论证而非说教, 道德论证 Truby, 主题统一性, 这到底在讲什么), (f) 类型 (类型惯例是对观众的承诺, Snyder 10 类故事, 颠覆 vs 尊重套路, 类型片 vs 文艺片, 中国类型 主旋律 / 古装 / 年代 / 悬疑 / 甜宠 / 都市 / 军旅 / 历史正剧), (g) 格式与工业流程 (好莱坞剧本格式与 Final Draft, logline 一句话故事, treatment 故事大纲, 节拍表, 分场 / 分集大纲, spec 原创剧本 vs 委托, pitch, coverage, 美剧编剧室与 showrunner 制; 中国 大纲→人物小传→分集大纲→剧本, 长剧集 40 集结构, 网络电影 / 网大, 分账剧, 平台定制剧, 微短剧竖屏短剧), (h) 改稿与开发 (写作就是改写, 改稿 / 润色 / 推倒重写, 处理意见 / 改稿意见, 片方与平台 notes, 杀死你的宝贝, 围读, 开发地狱), (i) 改编 (IP改编 小说 / 漫画 / 游戏改编, 忠于精神而非字句, 压缩, 中国网文 IP 热), (j) 中国影视编剧产业现实 (审查 / 广电总局约束, 备案 / 立项, 平台定制剧 爱优腾芒, 分账, 编剧维权 署名权 / 欠薪 / 枪手, 注水剧, 流量 + 大IP 资本逻辑 vs 原创工艺, 导演中心制 vs 编剧话语权), (k) 编剧职业与工艺生涯 (spec vs 委托, 编剧 vs 编审 / 策划, 单兵 vs 编剧室, 在开发链条中的位置, WGA 与署名仲裁规范, 入行, 中国编剧地位与权益)。跨 电影 / 美剧流媒体 / 中国电影与长剧集。不含 导演 / 摄影 / 制片 / 融资 / 表演 / 电影理论批评为终点 / 泛小说写作 / 纪录片 / 新闻 —— 本 skill 是「戏剧化编剧」工艺: 故事 / 人物 / 场景 / 对白 / 主题 / 结构 / 格式 与围绕它们的产业流程。 (Scriptwriting / Screenwriting for film & TV (影视编剧) — the cognitive operating system of practitioners who write the dramatic blueprint of films, television, and streaming series: the discipline of deciding WHAT story is told, WHO the characters are and why they change, HOW the scenes are dramatized, and WHY it matters thematically — distinct from directing (staging/visual realization), producing (financing/scheduling), and prose fiction (which has no format/scene/visual-action constraints). Covers (a) story & structure theory (Aristotle's Poetics — plot/character/thought + reversal peripeteia/recognition anagnorisis + catharsis; Syd Field's paradigm/three-act/plot points; Freytag's pyramid; Lajos Egri's premise; Robert McKee's Story — controlling idea/the gap/value charge/inciting incident/progressive complications; John Truby's 22 steps & moral argument; Christopher Vogler/Joseph Campbell hero's journey; Blake Snyder's Save the Cat 15-beat sheet; Dan Harmon's story circle; John Yorke's 5-act Into the Woods; Frank Daniel's 8-sequence method; 起承转合 East-Asian dramatic structure), (b) character (want vs need/external goal vs internal lack, character arc positive/negative/flat, 人物弧光, flaw-wound-ghost backstory, agency active vs passive protagonist, Egri's 3-dimensional character physiology/sociology/psychology, antagonist as the protagonist's mirror, ensemble & relationship webs, character revealed through choice under pressure), (c) dialogue (subtext 潜台词, dialogue as action & conflict not information, 'on the nose' avoidance, distinct character voice, exposition handling, Mamet/Sorkin intention-obstacle dialogue, show-don't-tell, 台词 craft in Chinese drama), (d) scene & sequence craft (scene as a mini-story with goal/conflict/turn, scene value charge & turning point, enter-late-leave-early, the 8-sequence method, set pieces, transitions, slug line/action line/parenthetical format craft), (e) theme & premise (controlling idea/premise/前提, theme as dramatized argument not message, moral argument Truby, thematic unity, 'what is this really about'), (f) genre (genre conventions as audience promise, Snyder's 10 story types, subverting vs honoring tropes, 类型片 vs 文艺片, Chinese genres 主旋律/古装/年代/悬疑/甜宠/都市/军旅/历史正剧), (g) format & industry process (Holly

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。

音乐制作 / 混音 (音乐制作 / 混音 (Music Production & Mixing) — 录音棚与卧室工作室里把一首歌从编曲/录音/编程做到混音/母带成品的工程+艺术认知操作系统，面向制作人(producer)、混音师(mixing engineer)、母带工程师(mastering engineer)、beatmaker、唱作人/bedroom producer，以及想入行/服务这行(录音棚、plugin 厂商、sample 公司)的视角。覆盖: (a) 第一性张力 — **服务歌曲/情绪 (serve the song / emotion-first: 技术只为打动人，'if it sounds good it is good'，用耳朵不用眼睛) ⇄ 技术正确/工程纪律 (technical correctness: gain staging 增益结构、headroom 余量、相位 phase、监听校准、LUFS 响度规范)**; **黄金耳朵/直觉混音 (mix by ears, reference-driven, 不看分析仪) ⇄ 看表/分析仪/规则 (mix by metrics: EQ 曲线、频谱仪 spectrum analyzer、相关计 correlation meter)**; **少即是多/减法混音 (subtractive, 'less is more', 录好源头 = 混音成功一半) ⇄ 重度处理/'we'll fix it in the mix' (heavy processing, 后期补救)**; **In-the-box 全数字 (ITB: DAW + 插件，召回方便，bedroom 可达专业) ⇄ 模拟硬件/outboard (analog console + 硬件，'mojo'/谐波染色 vs 召回噩梦)**; **人性化/groove/不完美 (humanize, push/pull, 'the feel') ⇄ 量化/网格/修音 (quantize to grid, pitch-correct, 'in the pocket' 靠编辑)**; (b) 核心工作流 / pipeline (最标准、最易蒸高质量+CLI 化) — 编曲制作 arrangement/production → 录音/编程 tracking/programming → 编辑 editing (comping 选段/quantize/pitch-correct/time-align) → 混音 mixing (gain staging → balance 平衡 → EQ → compression → 空间 reverb/delay → 自动化 automation → 总线/母线处理 bus/mix-bus) → 母带 mastering (响度/EQ/限制 limiting/dither/排序+间隔) → 交付 delivery (DDP/streaming spec/stems); (c) 工具栈 — DAW (Pro Tools 录音棚标准/Ableton Live 电子+现场/Logic Pro Mac 性价比/FL Studio beatmaker/Cubase/Studio One/Reaper); 插件 (EQ: FabFilter Pro-Q/SSL/API; 压缩: 1176/LA-2A/SSL bus comp 及其复刻 Waves/UAD/Plugin Alliance; 混响: Valhalla/Lexicon/Bricasti; 调音: Auto-Tune/Melodyne; 限制器 limiter: Pro-L 2/Ozone); 硬件 (监听音箱 monitors: Yamaha NS-10/Genelec; 声学处理 acoustic treatment; 转换器 converters: Apollo/RME; 话筒 mics: U47/SM7B/57); 采样/音色 (Splice/sample packs/Kontakt/Serum 合成器); (d) 知识正典 — Mixing Secrets for the Small Studio (Mike Senior)、The Mixing Engineer's Handbook / Recording Engineer's Handbook (Bobby Owsinski)、Zen and the Art of Mixing (Mixerman)、The Art of Mixing (David Gibson 可视化)、Modern Recording Techniques、Sound on Sound 杂志、Mix With The Masters 大师课、Pensado's Place; (e) figures/流派 — 混音大师 (Chris Lord-Alge CLA 摇滚/Andrew Scheps 'Stadium' 3-bus/Tony Maserati/Manny Marroquin/Serban Ghenea 流行隐形混音/Michael Brauer multing); 制作人 (Rick Rubin 减法/氛围、Quincy Jones、Dr. Dre 完美主义、Max Martin 流行结构、Jack Antonoff、Finneas bedroom→Grammy、Metro Boomin/trap、Timbaland、Pharrell); 母带 (Bob Katz K-system/响度战争批判、Bob Ludwig、Greg Calbi); 教育者 (Mike Senior、Pensado、Warren Huart Produce Like A Pro、Dan Worrall 技术深挖); (f) 行业话术/黑话 — gain staging/headroom/LUFS/true peak/comping/bouncing/printing/stems/DI/reamp/sidechain/parallel compression 并行压缩/mid-side/bus/aux/send-return/dry-wet/transient/sibilance/de-ess/pumping/mud 浑浊/harsh 刺耳/boxy/muddy/in the pocket/the pocket/quantize/swing/groove/vibe/mojo/reference track/A/B/recall/print/glue 胶水; (g) 争议/批判 — 响度战争 loudness war (Bob Katz/Loudness Penalty/streaming 归一化 LUFS 终结了吗)、修音/Auto-Tune 之争 (artistic vs cheating)、ITB vs 模拟玄学 (硬件 'warmth' 是否安慰剂、null test 盲测)、preset/AI 混音 (iZotope/LANDR/sample-based 是否毁了 craft)、bedroom producer 民主化 vs 录音棚消亡、'loudness'/over-compression、plugin 复刻 vs 真硬件、Spotify normalization 对母带的影响、过度依赖 reference/抄袭; (h) 创意 vs 技术张力是本行业 deep tacit 知识的核心 — 大量隐性 '听感' 知识难以言传，靠 reference/学徒/千小时积累。不含: 现场扩声 live sound/PA、音乐理论/作曲 composition (虽相关但聚焦录音棚后期制作)、配乐/film scoring (虽相关但聚焦歌曲制作)、纯硬件电子工程/合成器 DIY、音乐商业/版权/发行 (虽相关但聚焦制作技艺本身)。) Master OS — automated mastery of 音乐制作 / 混音 (Music Production & Mixing) — 录音棚与卧室工作室里把一首歌从编曲/录音/编程做到混音/母带成品的工程+艺术认知操作系统，面向制作人(producer)、混音师(mixing engineer)、母带工程师(mastering engineer)、beatmaker、唱作人/bedroom producer，以及想入行/服务这行(录音棚、plugin 厂商、sample 公司)的视角。覆盖: (a) 第一性张力 — **服务歌曲/情绪 (serve the song / emotion-first: 技术只为打动人，'if it sounds good it is good'，用耳朵不用眼睛) ⇄ 技术正确/工程纪律 (technical correctness: gain staging 增益结构、headroom 余量、相位 phase、监听校准、LUFS 响度规范)**; **黄金耳朵/直觉混音 (mix by ears, reference-driven, 不看分析仪) ⇄ 看表/分析仪/规则 (mix by metrics: EQ 曲线、频谱仪 spectrum analyzer、相关计 correlation meter)**; **少即是多/减法混音 (subtractive, 'less is more', 录好源头 = 混音成功一半) ⇄ 重度处理/'we'll fix it i

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。

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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。