「aso」の検索結果

Expertise in F2P economics, virtual currencies, and ethical monetization strategiesUse when "game monetization, F2P economy, in-app purchase, IAP strategy, battle pass design, loot box, gacha system, virtual currency, player LTV, whale monetization, game economy balance, premium currency, season pass, daily rewards, pay to win, ethical monetization, monetization, f2p, free-to-play, iap, in-app-purchase, battle-pass, season-pass, gacha, loot-box, virtual-economy, game-economy, ltv, arpu, retention, whales, pricing, microtransactions" 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。

企业财务与 CFO 视角 (企业财务与 CFO 视角 (Corporate Finance & the CFO Lens) — 面向创业公司与中小企业主/创始人/业务负责人的『看懂钱、管住钱、用好钱』的财务判断,不是考注会/中级职称的准则背诵,也不是投行卖方并购执行或 VC 投资人的看项目视角。覆盖: (a) 第一性张力 — 这行的核心世界观分歧: **利润是观点,现金是事实(权责发生制下的利润由收入确认时点、折旧摊销年限、存货计价、资本化与费用化的选择拼出来,是一组可辩论的判断;银行户头的钱是唯一不能辩论的事实——所以 CFO 看三张表的顺序是现金流量表→资产负债表→利润表,与外行相反) ⇄ 增长本身要烧钱(账面盈利的公司照样会因营运资金被增长吸干而倒闭:先付供应商、后收客户钱,规模越大缺口越大,这是『增长性破产』;所以现金转换周期比毛利率更早预警) ⇄ 记账合规派 vs 管理决策派(一套账是给税局与审计看的准则语言,另一套视图是给经营者看的贡献边际与单位经济;同一笔成本在两种语言里归属不同,把合规科目直接拿来做定价决策是中小企业最常见的错) ⇄ 全成本分摊 vs 贡献边际(把固定成本按产量分摊进单件成本,会在淡季得出『卖一件亏一件所以停产』的错误结论;边际思维只问增量收入是否覆盖增量成本,但长期只看边际会让公司永远收不回固定成本) ⇄ 预算是承诺 vs 预算是地图(传统年度预算把数字变成考核契约,导致部门年底突击花钱与藏预算;滚动预测与超越预算派主张预算只是当前最好的猜测,该月月刷新) ⇄ 融资是里程碑 vs 融资是负债(融资新闻稿把估值当成绩,但优先股、优先清算权、对赌与回购条款让创始人在低价退出时可能一分不拿;自筹派认为最便宜的钱是客户的预付款) ⇄ 估值方法之争(DCF 的数学严谨但对增长率与折现率假设极敏感,业内讥为『垃圾进垃圾出』;可比公司倍数简单但把市场情绪打包进来;早期公司两者都不成立,实际靠谈判与稀释目标倒推) ⇄ EBITDA 是不是有用(PE 与并购圈把它当经营现金流代理,巴菲特与芒格公开斥其忽略了折旧背后真实的资本开支;调整后 EBITDA 的『加回』项在业内被视为高危信号) ⇄ 财务是记分员 vs 财务是业务伙伴(传统财务事后出报表,财务 BP/FP&A 主张财务应在决策前进场做定价、投产、招人的经济性测算) ⇄ 中国中小企业的两套账现实 vs 合规红线(金税四期与社保入税之后,业内公认的做法是尽早并账,但这条张力必须如实呈现而不是装作不存在,也绝不给出规避税收的操作建议)); (b) 工具栈(记账层与决策层是两套东西) — 记账与 ERP(用友、金蝶、Odoo、QuickBooks、Xero、NetSuite、SAP Business One)、中国财税合规(电子税务局、金税四期发票与进销项比对、百望/航天信息电子发票、慧算账等代账 SaaS、个税与社保申报)、FP&A 与预算(Excel 与 Google Sheets 仍是绝对主力,之上是 Cube、Causal、Jirav、Mosaic、Runway、Abacum、Pigment、Anaplan、Planful)、现金流预测(Float、Fathom、13 周滚动现金流模板)、股权与 cap table(Carta、Pulley、AngelList、Excel 稀释模型,中国的股权代持与持股平台)、订阅计费与收入确认(Stripe Billing、Chargebee、Maxio)、费控报销(Ramp、Brex、Expensify、汇联易、分贝通)、BI 与看板(Power BI、Tableau、Metabase、帆软)、以及最被低估的纸笔工具(一页纸的驱动因素模型、贡献边际表、13 周现金日历)—— 选型的真正分岔是『公司在哪个阶段、由谁来维护这个模型』,不是厂商功能清单; (c) 心智模型层 — 三张表的勾稽关系(利润表的净利经现金流量表调整后落到资产负债表的未分配利润)、权责发生制与收付实现制的差、现金转换周期 CCC 与 DSO/DIO/DPO、营运资金与增长的耦合、贡献边际与盈亏平衡点、经营杠杆与固定成本结构、单位经济与 LTV/CAC 及回本周期、烧钱率与现金跑道 runway、自由现金流与业主收益 owner earnings、资本成本与机会成本、净现值与内部收益率、投入资本回报率 ROIC 与增长的价值条件(只有 ROIC 高于资本成本时增长才创造价值)、股权稀释与优先清算权的退出瀑布、递延收入是负债不是收入; (d) 工作流/SOP — 月度关账与管理报表包(关账日历、计提、对账、出具一页纸经营分析)、13 周滚动现金流预测的搭建与每周刷新、年度预算与滚动预测(自上而下目标与自下而上驱动因素模型的对撞)、定价与成本核算(标准成本、作业成本法、贡献边际定价与报价审批)、应收账款与账期管理(信用政策、账龄表、催收节奏、保理与供应链金融)、融资轮次建模(投前投后估值、期权池扩容对创始人的额外稀释、SAFE 与可转债转股、优先清算权下的退出分配)、投资决策与产能/招人测算(增量现金流、回收期、敏感性分析)、税务合规日历与汇算清缴、董事会与投资人财务包、尽调与数据室准备、以及财务模型的三表联动搭建; (e) 知识正典(en 一手极厚,中文一手集中在高校教授与准则原文) — 《Financial Intelligence》Berman & Knight(给非财务经理的入门标准)、《Financial Statements》Thomas Ittelson、Brealey·Myers·Allen《Principles of Corporate Finance》(公司金融教科书)、Damodaran 的估值三部曲与《Narrative and Numbers》及其 NYU 公开课与免费数据集、《Simple Numbers, Straight Talk, Big Profits!》Greg Crabtree(中小企业实操)、《Venture Deals》Feld & Mendelson(条款与稀释)、《Financial Shenanigans》Howard Schilit(识别财务粉饰)、《The Outsiders》Thorndike(资本配置)、《Accounting for Value》Penman、伯克希尔股东信中的业主收益与商誉摊销讨论、《The Essays of Warren Buffett》、《Profit First》Michalowicz(流行但有争议)、IFRS 15/16 与 ASC 606 收入与租赁准则原文、中国企业会计准则 CAS 与小企业会计准则、肖星《一本书读懂财报》与清华的财务分析公开课、张新民的财务报表分析体系; (f) 行业大佬/figures — Aswath Damodaran(NYU,估值教父,博客与公开课与数据集全免费开放,一手素材极厚)、Michael Mauboussin(ROIC 与资本配置的实证写作)、Howard Schilit(财务舞弊识别)、Karen Berman 与 Joe Knight(财务素养普及)、Greg Crabtree(中小企业现金与利润实操)、Brad Feld 与 Jason Mendelson(创业融资条款)、David Skok 与 Jason Lemkin 与 David Sacks(SaaS 单位经济与烧钱效率指标)、Warren Buffett 与 Charlie Munger(对 EBITDA 与股权激励费用化的著名批评)、CJ Gustafson 等现役 CFO 的时事通讯作者、以及中文圈的肖星与张新民等高校学者; (g) 争议/批判(必须保留不洗白) — 调整后 EBITDA 与非公认会计准则指标的滥用(把股权激励与一次性费用年年加回)、DCF 对假设的极端敏感与被用来事后合理化结论、独角兽估值与优先清算权造成的『纸面身价』幻觉、对赌与回购条款把股权融资变成隐性债务、Profit First 现金分桶法被专业会计批评为回避真实成本结构、作业成本法的实施失败率高、预算游戏与年底突击花钱、财务 BP 沦为报表美化、中国中小企业两套账的历史现实与金税四期后的合规收敛(如实呈现风险,不提供规避操作)、以及『融资额等于成功』的媒体叙事对创始人的误导; (h) 流派/思想谱系 — **准则与合规派(IASB/FASB/财政部,信可比性与审计留痕,语言是准则条文)** vs **管理会计/决策派(IMA 与贡献边际、作业成本法、有效产出会计,信决策相关性高于合规一致性)** vs **公司金融/估值派(Brealey-Myers-Allen 与 Damodaran,信现金流折现与资本成本)** vs **价值投资/资本配置派(巴菲特-芒格-Thorndike-Mauboussin,信业主收益与 ROIC,公开鄙视 EBITDA)** vs **创业与 SaaS 指标派(Skok-Lemkin-Sacks-Bessemer,信单位经济、回本周期与烧钱倍数)** vs **中小企业现金实操派(Crabtree、Profit First 一脉,信老板看得懂的少数几个数)**。不含: 投行卖方并购执行与尽调建模(已由 investment-banking-mna 覆盖)、VC 投资人的看项目与投后视角(已由 vc-investor 覆盖)、个人理财与二级市场投资(已由 personal-investing 覆盖)、注册会计师考证与准则条文背诵、以及任何税收规避操作建议。) Master O

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。

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.

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。

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

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。

Optimize App Store and Google Play listings via a 7-phase, plan-approval-gated ASO workflow (keyword strategy, metadata, localization). Don't use for web SEO, paid UA campaigns, or pre-submission compliance audits.

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。

Applies the reasoning of Mary Wollstonecraft (18th-century English philosopher and author of A Vindication of the Rights of Woman) to evaluate situations involving power dynamics, education, independence, gender roles, and systemic inequality. Use this skill whenever Claude encounters career trade-offs involving financial dependence, analyzing structural oppression, questioning societal norms, or balancing reason against emotion. It helps dismantle arbitrary hierarchies, prioritize rational capability over superficial elegance, and frame personal struggles as political realities.

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。

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

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。

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.

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。

Suede Labs Google Play delivery skill: ship an Android release end to end from the agent interface, without opening the Play Console. Set up credentials, upload an AAB, promote between tracks, stage or complete a rollout, push per-locale release notes, and prove against the Play Developer API what is actually live. One step stays a Console action by design and the skill hands it to you: granting the service account release access the first time. Use when uploading or promoting an Android build, wiring a Play service account and fastlane supply lanes, fixing per-versionCode changelogs, raising or halting a staged rollout, or answering what version and fraction production is really serving. NOT FOR: planning or building the app itself (use android-app-factory); live listing and keyword audits (use suede-aso); CI required checks (use suede-ci-gate); iOS release (a private Suede Labs companion, not in this pack: ios-app-store-release).

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。

Suede Labs Android app factory: plan, build, test, and release a production-grade native Android app from a product idea through Google Play. Use for requests to create, ship, submit, monetize, or modernize an Android app. Covers Kotlin and Jetpack Compose architecture, API-level policy verification, accessibility, privacy and Data Safety, Play Billing, Play Integrity, account deletion, testing, performance, store assets, signing, staged rollout, and a release evidence gate. NOT FOR: iOS work (private Suede Labs companion, not in this pack: ios-app-factory), a review-only pass on an existing app (use suede-code-review), or live Play listing and keyword audits on a shipped app (use suede-aso).

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。

Suede Labs workflow for turning a website, PWA, dashboard, or marketplace into an iOS app. Use when the user has a live site or web app and asks to put it on the App Store, wrap it in an app, ship an iOS version, or convert a PWA to native, covers URL audit, shell-vs-native strategy, App Store 4.2 wrapper risk, native value requirements, screenshots, metadata, privacy answers, and the release gate. NOT FOR: building a native iOS app with no existing site (private Suede Labs companion, not in this pack: ios-swiftui-product); repairing or releasing an existing Capacitor shell (private Suede Labs companion, not in this pack: ios-capacitor-shell); Android conversions (use android-app-factory); live listing and keyword audits on a shipped app (use suede-aso).

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。

Suede-owned marketing image production for generation prompts, hero and social graphics, product mockups, export sizing, compression, and preview assets. Use when the user needs a general-purpose marketing image or an image-production workflow. NOT FOR: paid-ad creative systems (use suede-ad-creative), video production (use suede-video), or app-store listing strategy (use suede-aso).

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。

Suede-owned app-store optimization discipline for keyword fields, titles, subtitles, descriptions, screenshots, ratings context, and competitor listing audits. Use when improving App Store or Google Play visibility or listing conversion from a live app URL and current console evidence, or when authoring keyword, name, subtitle, and promo fields for an app that has not shipped yet. NOT FOR: building or releasing the app (use android-app-factory or site-to-ios-app; native iOS builds are a private Suede Labs companion, not in this pack: ios-app-factory), creating paid ad assets (use suede-ad-creative), or install-event instrumentation (use suede-analytics).

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。

Brainstorms and debates approaches, then drives toward an actionable decision. Use whenever someone needs a thinking partner for a decision they're facing: 'discuss', 'debate', 'brainstorm', 'weigh options', 'tradeoffs', 'should I do X or Y', 'help me decide', 'I'm torn between', 'sanity check my thinking', or 'what do you think about'. The user must be asking for help reasoning through a choice — not asking to build, fix, evaluate, plan, or modify something (even if the topic involves this skill itself). Picks the right decision lens, surfaces tradeoffs and blind spots, pushes back when reasoning is genuinely weak, and never implements.

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 considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.

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。

Step 2 of debugging: reason about root cause based on observed symptoms.

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。

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.

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。

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

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。

When the user wants to audit or optimize an App Store or Google Play listing. Also use when the user mentions 'ASO audit,' 'app store optimization,' 'optimize my app listing,' 'improve app visibility,' 'app store ranking,' 'audit my listing,' 'why aren't people downloading my app,' 'improve my app conversion,' 'keyword optimization for app,' or 'compare my app to competitors.' Use when the user shares an App Store or Google Play URL and wants to improve it.

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。

Google Trends keyword search popularity comparison and trend analysis, supporting global regions and custom time ranges. Triggered by: Google Trends, keyword popularity over time, search interest comparison, keyword trend analysis, seasonal trend detection, regional search popularity, keyword heatmap, multi-keyword comparison on Google, keyword research, market trend analysis, search trends, seasonal analysis, regional popularity.

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。

Nexscope Ozon category product search: fetches the product list for a given Ozon category ID, returning category-level aggregates (total sales, total revenue, average price, average rating, seasonality) and per-product sales, price, rating, review count, brand, seller, and fulfillment method. Use for category selection analysis, category bestseller mining, category capacity and price band analysis, seasonality assessment. Trigger when the user mentions Ozon category products, Ozon category analysis, Ozon category selection, Ozon category bestsellers, Ozon category total sales, Ozon category average price, Ozon category search, Ozon category products, category best-sellers, category analysis. Also trigger when the intent is to view products and category-level summary data within an Ozon category, even without explicitly mentioning Nexscope.

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。

Nexscope keyword historical search volume query, returning Amazon keyword exact search volume trends in 7-day periods, covering 10 marketplaces including US, UK, DE, JP, etc. Trigger when the user mentions keyword search volume trends, historical search volume, search popularity changes, keyword seasonality, search volume fluctuations, Nexscope search volume, keyword search volume history, keyword trend, search volume over time, seasonal search volume, keyword popularity trend. Even if the user does not explicitly mention "Nexscope", if their need involves viewing the search volume trend of an Amazon keyword over time, this skill should also be triggered.

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。

Multi-dimensional Amazon product search and filtering based on Nexscope data, covering 14 marketplaces, with support for historical monthly snapshot lookback. Trigger when the user mentions Nexscope product search, Amazon product filtering, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot review, product search, monthly sales/revenue, ABA keyword product discovery, price range filtering, new product discovery, multi-condition combined filtering, product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot. Even if the user does not explicitly mention "Nexscope", if their need involves Amazon product search, filtering, comparison, or product exploration by category/brand/seller dimensions, this skill should also be triggered.

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。

Query and analyze Amazon ABA (Brand Analytics) search term data, covering 15 marketplaces with nearly 3 years of weekly data. Trigger when the user mentions ABA data, Amazon search term analysis, keyword mining, search ranking trends, market opportunity analysis, seasonal keywords, high-click low-conversion analysis, blue ocean keyword discovery, competitor keyword analysis, ABA data, search term report, keyword mining, search ranking trends, blue ocean keywords, click share, conversion share, seasonal keywords, market opportunity analysis, competitor keywords. Even if the user does not explicitly mention "ABA", if their need involves Amazon search term data and ranking analysis, this skill should also be triggered.

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。