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It's 11pm before your launch. Your PH page is ready but you have no idea what actually moves the ranking algorithm. Upvotes? Comments? Time-of-day? This is the hour-by-hour operations manual from someone who's coached 30+ #1 finishes. What's inside: • Ranking algorithm deep-dive (it's not just upvotes — weighted factors decoded) • Launch day minute-by-minute checklist (PST timing, first 3 hours are critical) • Voter mobilization strategies (ethical, anti-spam-safe approaches) • Asset preparation templates (gallery, tagline ≤60 chars, maker comments) • Post-launch 72h momentum plan (convert PH traffic → retained users) Built from: 30+ PH #1 daily wins, 10+ weekly top 3, 2 monthly top 5. 3,000-5,000+ upvotes per launch. Triggers: "Product Hunt" | "PH launch" | "Product Hunt #1" | "PH ranking" | "Product Hunt strategy" | "PH upvotes" | "launch day" | "PH打榜" | "Product Hunt攻略" | "PH ranking algorithm"

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🇺🇸 Reddit Marketing & Growth Playbook 2026 — The complete Reddit operations SOP for AI/SaaS founders. Covers account warming (Karma 0→500 in 20 days), shadow ban prevention, multi-account matrix via fingerprint browsers, subreddit selection across 10K+ communities, content templates (90/10 rule), Product Hunt × Reddit flywheel, AMA strategy. Why this matters NOW: Reddit content is 40.11% of ChatGPT/Claude training data — the highest-weighted English UGC source. Battle-tested by AFFiNE Reddit campaigns generating 3-4万有效曝光 with 5-8% GitHub Star conversion, plus 7 case studies (Adobe 3x conversion, Base44 $80M AMA, SenseNova-U1 multi-sub launch, Starterstory 0→3K users). 🇨🇳 Reddit 运营增长实战手册 — AI/SaaS 出海 founder 的 Reddit 完整 SOP。覆盖账号体系(20天养号 Karma 0→500)、影子封禁防御、指纹浏览器矩阵、10万+ subreddits 筛选、内容模板(90/10 法则)、Product Hunt × Reddit 飞轮、AMA 打法。**为什么现在做:Reddit 内容占 ChatGPT/Claude 训练数据 40.11%,是最高权重的英文 UGC 来源**。基于 AFFiNE Reddit 实战 3-4 万曝光 + 5-8% Star 转化,含 7 个完整案例(Adobe 3x 转化、Base44 $80M AMA、SenseNova-U1 多社区联动、Starterstory 0→3K 用户冷启动)。 🇯🇵 Reddit マーケティング＆グロースプレイブック — AI/SaaS創業者向けの完全なReddit運用SOP。アカウント育成（20日でKarma 0→500）、シャドウBAN防止、フィンガープリントブラウザマトリックス、サブレディット選定、コンテンツテンプレート（90/10ルール）、Product Hunt × Redditフライホイール、AMA戦略をカバー。**重要な理由：Reddit コンテンツは ChatGPT/Claude のトレーニングデータの40.11%を占める英語 UGC 最大の情報源**。AFFiNE Redditキャンペーン3-4万インプレッション＋5-8% GitHubスター変換で実証。7つの実例（Adobe 3倍変換、Base44 $80M AMA、SenseNova-U1、Starterstory 0→3Kユーザー）。 🇰🇷 Reddit 마케팅 & 그로스 플레이북 — AI/SaaS 창업자를 위한 완전한 Reddit 운영 SOP. 계정 워밍업(20일 Karma 0→500), Shadow Ban 방지, 핑거프린트 브라우저 매트릭스, 서브레딧 선정, 콘텐츠 템플릿(90/10 룰), Product Hunt × Reddit 플라이휠, AMA 전략을 다룹니다. **지금 해야 하는 이유: Reddit 콘텐츠는 ChatGPT/Claude 학습 데이터의 40.11%를 차지하는 최대 영어 UGC 소스**. AFFiNE Reddit 캠페인 3-4만 노출 + 5-8% GitHub Star 전환으로 검증. 7가지 사례 연구(Adobe 3배 전환, Base44 $80M AMA, SenseNova-U1, Starterstory 0→3K 사용자). Triggers: "reddit marketing" | "reddit growth" | "reddit ads" | "reddit advertising" | "reddit strategy" | "reddit promotion" | "subreddit marketing" | "reddit playbook" | "reddit SOP" | "reddit shadow ban" | "shadow ban prevention" | "reddit karma" | "reddit AMA" | "reddit product launch" | "reddit AI training data" | "reddit GEO" | "AFFiNE reddit case" | "Base44 AMA" | "SenseNova Reddit" | "subreddit selection" | "r/SaaS posting" | "r/MachineLearning self-promotion" | "fingerprint browser matrix" | "AdsPower reddit" | "reddit account farming" | "reddit 90/10 rule" | "reddit content strategy" | "reddit indie founder" | "reddit cold start" | "Reddit 运营" | "Reddit 营销" | "Reddit 防封" | "Reddit 矩阵号" | "Reddit 出海" | "Reddit 引流" | "Reddit 冷启动" | "影子封禁" | "Reddit Karma" | "Reddit 养号" | "Reddit AMA" | "Reddit マーケティング" | "Reddit グロース" | "Reddit 마케팅" | "Reddit 그로스"

🇺🇸 B2B SaaS Growth — PLG vs SLG Playbook — Diagnose whether your problem is distribution, pricing, or PMF. PLG/SLG selection by ACV and sales cycle, the 5-stage path from $0 to $10M ARR, NRR discipline, affiliate & channel motion, enterprise tiering. Built from HeyGen, Deel, Vercel, Supabase, Snowflake patterns. 🇨🇳 B2B SaaS 增长 — PLG vs SLG 决策手册 — 诊断你的瓶颈是分发、定价还是 PMF。按 ACV 和销售周期选 PLG/SLG，$0 → $10M ARR 的 5 阶段路径，NRR 纪律，联盟与渠道打法，Enterprise 分层。提炼自 HeyGen、Deel、Vercel、Supabase、Snowflake。 🇯🇵 B2B SaaS グロース — PLG vs SLG プレイブック — 課題が流通・価格・PMFのどれかを診断。ACVとセールスサイクルでPLG/SLG選定、$0→$10M ARRの5段階パス、NRR規律、アフィリエイト＆チャネル。 🇰🇷 B2B SaaS 성장 — PLG vs SLG 플레이북 — 병목이 유통·가격·PMF 중 무엇인지 진단. ACV와 세일즈 사이클로 PLG/SLG 선택, $0 → $10M ARR 5단계 경로, NRR 규율, 제휴 & 채널. Triggers: "B2B growth" | "B2B SaaS" | "PLG" | "SLG" | "product-led growth" | "sales-led growth" | "PLG or SLG" | "SaaS pricing" | "ARR growth" | "NRR" | "go to market" | "enterprise sales" | "affiliate" | "PMF" | "B2B 增长" | "PLG 还是 SLG" | "SaaS 定价" | "渠道合作" | "PLG/SLG 선택"

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"

🇺🇸 Your dev team ships features nobody asked for while user-reported bugs pile up for months. Operations blames engineering for ignoring users; engineering blames operations for not understanding technical constraints. This gives you the complete Product × Engineering × Operations alignment SOP — from unified backlog to 10-day sprint cadence to veto power rules. What's inside: • Dual-layer Kanban system (master backlog + sprint board with unified tagging) • 10-day sprint standard process (Day 1 dev → Day 6 testable build → Day 10 ship) • Issue template with reproducibility requirements (3x reported = auto-severe) • Tri-party alignment meetings (daily standup / sprint planning / sprint review) • Operations veto power on releases (P0 bug = block shipping) • User feedback → product iteration closed loop (beta testing + interview SOP) • Core metrics framework (acquisition → activation → retention → monetization → referral) • Technical debt management (20-30% sprint capacity reserved) • Ready-to-use templates: Bug Report, Sprint Planning, Responsibility Matrix Built from: Real product strategy meetings + beta testing frameworks. References Supabase sprint model, Manus/DeepSeek commercialization alignment. By @WeiYipei. 🇨🇳 你的研发团队在做没人要的新功能，用户反馈的 Bug 堆了三个月没人动。运营觉得研发不听用户，研发觉得运营不懂技术。这份 SOP 给你从统一看板到 10 天迭代节奏到一票否决权的完整产研运协同框架。 🇯🇵 開発チームは誰も求めていない機能を作り、ユーザーから報告されたバグは何ヶ月も放置。このSOPは、統一バックログから10日スプリント、リリース拒否権まで、プロダクト×エンジニアリング×オペレーションの完全な連携フレームワークを提供します。 🇰🇷 개발팀은 아무도 요청하지 않은 기능을 만들고, 사용자가 보고한 버그는 몇 달째 방치됩니다. 이 SOP는 통합 백로그부터 10일 스프린트, 릴리스 거부권까지 제품×개발×운영 완전 협업 프레임워크를 제공합니다. Triggers: "product ops" | "engineering operations" | "product development SOP" | "sprint planning" | "iteration management" | "cross-functional alignment" | "product engineering ops" | "dev ops collaboration" | "产研运协同" | "迭代管理" | "产品研发运营" | "プロダクト開発運営" | "제품개발운영"

🇺🇸 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 complete community & ambassador operations SOP — 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. What's inside: • Pre-launch readiness checklist (6 conditions that must be true before starting) • 6-step community setup SOP (platform selection → rules → admin standards → monitoring → wiki → metrics) • Ambassador recruitment system (A+B qualification, application form design, scoring rubric) • 4-tier progression system (Bronze → Silver → Gold → Platinum with point thresholds) • 5-pillar incentive framework (Product quality → Beta access → Founder access → KOL path → Full engagement) • Churn early-warning system + retention playbook • Event operations SOP (6 event types × full lifecycle) • Health metrics dashboard (6 core KPIs + 5 ambassador-specific indicators) • Governance & risk control (behavior code, escalation matrix) • Real templates: recruitment post, welcome email, annual calendar 🇨🇳 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"

🇺🇸 GitHub README Writing System — Craft a README that converts visitors to stars in <3 seconds. Proven structure from AFFiNE's 0→60K star journey: tagline engineering, first-screen law, section-by-section copywriting guide, Claude Code integration section, anti-patterns, and a pre-publish checklist. Use when you need to write or rewrite a specific README file. 🇨🇳 GitHub README 写作系统 — 打造 3 秒内把访客转化为 star 的 README。来自 AFFiNE 0→60K star 实战：tagline 工程、首屏法则、逐节文案指南、Claude Code 集成板块、反模式、发布前自检清单。需要写或改一个具体 README 文件时使用。 🇯🇵 GitHub README 作成システム — 3秒以内にビジターをスターに変えるREADMEを作る。AFFiNE 0→60Kスター実績から: タグライン設計、ファーストスクリーン法則、セクション別ライティングガイド、Claude Codeインテグレーション、アンチパターン、公開前チェックリスト。 🇰🇷 GitHub README 작성 시스템 — 3초 안에 방문자를 스타로 전환하는 README 작성법. AFFiNE 0→60K 스타 실전: 태그라인 설계, 첫 화면 법칙, 섹션별 카피라이팅 가이드, Claude Code 통합 섹션, 안티패턴, 게시 전 체크리스트. Triggers: "write README" | "README template" | "GitHub README" | "project description" | "tagline" | "open source README" | "README structure" | "README review" | "fix README" | "rewrite README" | "README写作" | "写README" | "README模板" | "项目介绍" | "开源项目文案" | "改README" | "README检查" | "README 구조" | "README 작성" | "README 검토" | "READMEの書き方" | "READMEレビュー"

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"

Marketing playbook for open-source projects led by non-technical founders. Covers README optimization, community building, contributor attraction, and translating OSS traction into revenue. By @WeiYipei.

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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. Inside: 4-step research framework (website → social → traffic → ad spend) · 3-version Wayback evolution analysis · X/Twitter propagation-chain mapping · growth-flywheel 6-stage scoring · KOL identification · content-effectiveness ranking · ICP + freemium pricing teardown · self-check checklist. New in 1.2: time-machine competitor archaeology — Google date-range search back to pre-fame years, star-history launch-day reconstruction (AppFlowy ~40-channel zero-budget launch teardown), competitor funding news as a launch-timing signal, and the "open source alternative" positioning play. Sourced from first-hand founder interviews (AFFiNE co-founder, 2026-04, self-reported figures marked). 🇨🇳 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"

SEO/GEO Agent Operations SOP v2 — Rebuilt from real-world operations (analook.com 0→launch, GSC incident, DataForSEO monitoring, gingiris.tools post-migration recovery). What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily SEO log — first item is always GSC token status check • Data cross-validation rule: any external metric must come from ≥2 sources before use • Backlink progress tracking (6-week wait → check → alert if not indexed) • New vs. established site strategy matrix (new site <6mo: KD≤20; mature: KD up to 35+) Real incidents baked in: GSC token expired silently for 2 weeks (analook.com), P0 keywords dropped out of Top 100 after domain migration (gingiris.tools), traffic data off by 17× from single-source DataForSEO. Triggers: "SEO agent" | "SEO daily report" | "GSC monitoring" | "DataForSEO" | "GEO agent" | "backlink tracking" | "IndexNow" | "competitor comparison page" | "SEO SOP" | "autonomous SEO" | "GEO triple combo" 🇨🇳 SEO/GEO Agent 运营 SOP v2 — 基于真实运营经验重写（analook.com 从零建站 + GSC 断档 2 周 + DataForSEO 监控 + gingiris.tools 迁移权重恢复）。 对话式开局、强制日报（GSC token 是第一项）、数据交叉验证铁律、外链进度追踪、新老站区分策略。

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Twitter/X Agent Operations SOP v2 — Rebuilt from real dual-account operations. Real data: • CN account: grew from 1,150 → 3,679 followers (~14 months), 1 tweet/day, OAuth1 direct post • EN account: Buffer API • Real incidents: cron silent-failed for 2 weeks unnoticed, analytics data off by 17×, thread performance worse than single posts What's new in v2: • Step-by-step onboarding (Q1→Q6), multiple choice wherever possible — no big forms • Mandatory daily log after every tweet + weekly report every Monday • Pre-publish safety checklist (agent must pass before posting) • Content pool tracker (used/unused) + alert when ≤3 items remain • Dual-account credential separation (CN: OAuth1 / EN: Buffer API) • MASTER-STATUS.md as the single source of truth — read + write every session 🇨🇳 Twitter/X Agent 运营 SOP v2 — 基于真实双账号运营经验重写。 开局对话式收集 context、强制日报+周报、发推前红线自检、素材库追踪、双账号凭证分离、MASTER-STATUS.md 单一真相来源。 真实数据：中文账号从 1,150 粉增长至 3,679 粉（约14个月），1条/天。 Triggers: "twitter运营" | "推特agent" | "发推SOP" | "AI代运营" | "推文日报" | "素材库" | "Buffer API" | "OAuth1发推" | "twitter automation" | "tweet sop" | "推特涨粉"

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「Tell, Don't Ask」原則に基づくコードレビューと設計支援。オブジェクトの状態を問い合わせて 外部で判断するパターンを、オブジェクトに直接命じるパターンに変換する。カプセル化を強化し、 責任をデータを持つオブジェクトに集約する設計を促進する。コードレビュー、新規実装、 リファクタリング時にgetterの乱用やFeature Envyの改善が必要な場合に使用。 対象言語: Java, Kotlin, Scala, TypeScript, Python, Ruby, Go, Rust。 トリガー：「getterを減らしたい」「カプセル化を改善して」「Feature Envyを直して」 「オブジェクトに責任を持たせたい」「デメテルの法則」といったOOP設計関連リクエストで起動。

ファーストクラスコレクションパターンの設計・実装を支援。コレクションをラップする専用クラスの 設計、ドメインロジックの集約、不変性の確保をガイド。コードレビュー、新規実装、リファクタリング 時にコレクション操作ロジックが散在している場合に使用。 対象言語: Java, Kotlin, Scala, TypeScript, Python, Ruby, Go, Rust。 トリガー：「コレクションをラップしたい」「リストのロジックを集約」「ファーストクラスコレクション」 「コレクション操作が散在」「List<Order>をOrdersクラスに」といったコレクション設計関連リクエストで起動。

DDDにおけるリポジトリの設計ルールとアンチパターンを提供する。集約単位の命名規則、 CQS（Command Query Separation）に基づくメソッド設計、入出力の型制約をチェックする。 コードレビュー、新規実装、リファクタリング時にリポジトリ設計の問題を検出する場合に使用。 対象言語: 言語非依存（Java, Kotlin, Scala, TypeScript, Go, Rust, Python等すべて）。 トリガー：「リポジトリの設計をレビュー」「Repository名がおかしい」「findByIdの戻り値」 「リポジトリがDTOを返している」「テーブル名でリポジトリを作ってしまった」 「集約単位のリポジトリ」「リポジトリのアンチパターン」「リポジトリのCQS」 といったリポジトリ設計関連リクエストで起動。

デメテルの法則（最小知識の原則）に基づくコードレビューと設計支援。オブジェクトの連鎖呼び出し （Train Wreck）を検出し、直接の友人とのみ会話する設計へ変換する。結合度の低減と 変更容易性の向上を促進する。コードレビュー、新規実装、リファクタリング時に オブジェクト間の結合が深い場合に使用。 対象言語: Java, Kotlin, Scala, TypeScript, Python, Ruby, Go, Rust。 トリガー：「デメテルの法則」「連鎖呼び出しを減らしたい」「Train Wreckを直して」 「結合度を下げたい」「ドット連鎖が多い」「最小知識の原則」「Law of Demeter」 といったオブジェクト間結合関連リクエストで起動。

DDDの集約(Aggregate)設計ルールに基づくコードレビュー・設計支援・リファクタリングを行う。 Evans Rules、Vernon's 4 Rules、Design by Contractに基づき、集約の境界定義、不変条件の検証、 不変(Immutable)設計、ID参照、結果整合性、ドメインイベント連携を包括的にガイドする。 以下のいずれかに該当する場合は必ずこのスキルを使用すること： - 集約(Aggregate)の新規設計・実装・リファクタリング（どの言語でも） - 既存の集約やエンティティクラスのDDD観点でのコードレビュー - 集約の境界決定（「AとBは同じ集約にすべきか？」「この集約は大きすぎるか？」） - 集約内の不変条件・整合性境界の設計 - 集約間の連携方式の判断（ドメインイベント、結果整合性、Sagaパターン） - 可変(Mutable)な集約コードを不変(Immutable)設計にリファクタリングする - publicフィールド、直接参照、push/appendなどカプセル化違反の検出・修正 キーワード例：集約、Aggregate、aggregate boundary、集約ルート、AggregateRoot、 エンティティ設計、DDD実装、Vernon Rules、Evans Rules、集約の分割、真の不変条件

Plan and run manual tests of the project's running app. Runs a session in one of five modes: exploratory, verification, smoke, assessment (UX, localization, accessibility, improvement review), or AI probe. Also writes a manual test plan that holds only what automated tests cannot judge. Use whenever the user asks, in any language, for something to be tested by hand or for a manual test plan — "manual test", "exploratory test", "bug hunt", "verify the bug fix", "smoke test", "QA this screen", "review this screen's UX", "what would you improve", "check the localized copy", "test the AI agent's answers", "write manual test cases", "kịch bản test manual" — or assigns a test design, test plan or test-case IDs to execute by hand. Not for writing automated tests.

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Produces requirement-by-requirement CRE insurance certificate compliance reviews by analyzing ACORD 25 certificates and endorsements against Access Agreement terms. Use when the user mentions COI review, insurance compliance, ACORD 25 analysis, Additional Insured verification, primary/non-contributory status, waiver of subrogation, vendor insurance audit, CGL compliance, umbrella follow-form, broker-ready deficiency instructions, certificate holder vs. additional insured, AI endorsements (CG 20 10, CG 20 37), or carrier rating checks.

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Apollo.io benefits packages by country — health insurance, equity, perks, and stipends

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The alphabetical-sort invariants the hyperlane-registry CI / CodeRabbit enforces on warp route YAML (deploy.yaml and config.yaml) — top-level chain entries sorted by chain name, and keys within each entry in strict alphabetical order — plus the canonical per-file key orderings and a verification pass. Referenced by any warp deploy/update skill that writes or edits a registry YAML file.

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Maintain the durable, per-ticket run log that warp deploy/update skills append to at every milestone — a Linear-document-by-title primary with single-writer discipline and a local-file fallback, a machine-parseable per-chain row plus prose entry shape, and a surface-the-URL-as-proof hard gate. Referenced by any warp deploy/update skill that must leave a retrospective trail across worker restarts.

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Helper skill for using Hyperlane CLI address conversion utilities (addressToBytes32 and bytes32ToAddress) for cross-chain message formatting

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