[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71897CJJMA5JKQSBSSR89F0":3,"skill-same:01M71897CJJMA5JKQSBSSR89F0":66},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":6,"ownerHtmlUrl":49,"ownerBlogUrl":50,"ownerDescription":6,"updatedAt":51,"install":52,"resources":65},"01M71897CJJMA5JKQSBSSR89F0","earnings-preview",null,"Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull\u002Fbear scenarios, and identify what will move the stock. Triggers on \"earnings preview\", \"what to watch for [company] earnings\", \"pre-earnings\", \"earnings setup\", or \"preview Q[X] for [company]\".","anthropics\u002Ffinancial-services","anthropics","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4","01M697XGDPXJAVQ8391V2BCYTE","Anthropic","01M7188Y8CSYMMZ40A4B4N518V",41274,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fagent-plugins\u002Fearnings-reviewer\u002Fskills\u002Fearnings-preview\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"earnings preview","earnings","preview","build","estimate","notes","with","reports","analysis","positioning","use","triggers","up","company","earnings analysis","frameworks","move","stock","for","SET","2026-11-10 10:12:30",false,"---\nname: earnings-preview\ndescription: Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull\u002Fbear scenarios, and identify what will move the stock. Triggers on \"earnings preview\", \"what to watch for [company] earnings\", \"pre-earnings\", \"earnings setup\", or \"preview Q[X] for [company]\".\n---\n\n# Earnings Preview\n\n## Workflow\n\n### Step 1: Gather Context\n\n- Identify the company and reporting quarter\n- Pull consensus estimates via web search (revenue, EPS, key segment metrics)\n- Find the earnings date and time (pre-market vs. after-hours)\n- Review the company's prior quarter earnings call for any guidance or commentary\n\n### Step 2: Key Metrics Framework\n\nBuild a \"what to watch\" framework specific to the company:\n\n**Financial Metrics:**\n- Revenue vs. consensus (total and by segment)\n- EPS vs. consensus\n- Margins (gross, operating, net) — expanding or contracting?\n- Free cash flow\n- Forward guidance vs. consensus\n\n**Operational Metrics** (sector-specific):\n- Tech\u002FSaaS: ARR, net retention, RPO, customer count\n- Retail: Same-store sales, traffic, basket size\n- Industrials: Backlog, book-to-bill, price vs. volume\n- Financials: NIM, credit quality, loan growth, fee income\n- Healthcare: Scripts, patient volumes, pipeline updates\n\n### Step 3: Scenario Analysis\n\nBuild 3 scenarios with stock price implications:\n\n| Scenario | Revenue | EPS | Key Driver | Stock Reaction |\n|----------|---------|-----|------------|----------------|\n| Bull | | | | |\n| Base | | | | |\n| Bear | | | | |\n\nFor each scenario:\n- What would need to happen operationally\n- What management commentary would signal this\n- Historical context — how has the stock moved on similar prints?\n\n### Step 4: Catalyst Checklist\n\nIdentify the 3-5 things that will determine the stock's reaction:\n\n1. [Metric] vs. [consensus\u002Fwhisper number] — why it matters\n2. [Guidance item] — what the buy-side expects to hear\n3. [Narrative shift] — any strategic changes, M&A, restructuring\n\n### Step 5: Output\n\nOne-page earnings preview with:\n- Company, quarter, earnings date\n- Consensus estimates table\n- Key metrics to watch (ranked by importance)\n- Bull\u002Fbase\u002Fbear scenario table\n- Catalyst checklist\n- Trading setup: recent stock performance, implied move from options\n\n## Important Notes\n\n- Consensus estimates change — always note the source and date of estimates\n- \"Whisper numbers\" from buy-side surveys are often more relevant than published consensus\n- Historical earnings reactions help calibrate expectations (search for \"[company] earnings reaction history\")\n- Options-implied move tells you what the market expects — compare to your scenarios\n","# Earnings Preview\n\n## Workflow\n\n### Step 1: Gather Context\n\n- Identify the company and reporting quarter\n- Pull consensus estimates via web search (revenue, EPS, key segment metrics)\n- Find the earnings date and time (pre-market vs. after-hours)\n- Review the company's prior quarter earnings call for any guidance or commentary\n\n### Step 2: Key Metrics Framework\n\nBuild a \"what to watch\" framework specific to the company:\n\n**Financial Metrics:**\n- Revenue vs. consensus (total and by segment)\n- EPS vs. consensus\n- Margins (gross, operating, net) — expanding or contracting?\n- Free cash flow\n- Forward guidance vs. consensus\n\n**Operational Metrics** (sector-specific):\n- Tech\u002FSaaS: ARR, net retention, RPO, customer count\n- Retail: Same-store sales, traffic, basket size\n- Industrials: Backlog, book-to-bill, price vs. volume\n- Financials: NIM, credit quality, loan growth, fee income\n- Healthcare: Scripts, patient volumes, pipeline updates\n\n### Step 3: Scenario Analysis\n\nBuild 3 scenarios with stock price implications:\n\n| Scenario | Revenue | EPS | Key Driver | Stock Reaction |\n|----------|---------|-----|------------|----------------|\n| Bull | | | | |\n| Base | | | | |\n| Bear | | | | |\n\nFor each scenario:\n- What would need to happen operationally\n- What management commentary would signal this\n- Historical context — how has the stock moved on similar prints?\n\n### Step 4: Catalyst Checklist\n\nIdentify the 3-5 things that will determine the stock's reaction:\n\n1. [Metric] vs. [consensus\u002Fwhisper number] — why it matters\n2. [Guidance item] — what the buy-side expects to hear\n3. [Narrative shift] — any strategic changes, M&A, restructuring\n\n### Step 5: Output\n\nOne-page earnings preview with:\n- Company, quarter, earnings date\n- Consensus estimates table\n- Key metrics to watch (ranked by importance)\n- Bull\u002Fbase\u002Fbear scenario table\n- Catalyst checklist\n- Trading setup: recent stock performance, implied move from options\n\n## Important Notes\n\n- Consensus estimates change — always note the source and date of estimates\n- \"Whisper numbers\" from buy-side surveys are often more relevant than published consensus\n- Historical earnings reactions help calibrate expectations (search for \"[company] earnings reaction history\")\n- Options-implied move tells you what the market expects — compare to your scenarios\n",{"name":5,"description":7},"main","60565064557ca77b12f62aa7877f365d111c129d","plugins\u002Fagent-plugins\u002Fearnings-reviewer\u002Fskills\u002Fearnings-preview",5748,"https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services","https:\u002F\u002Fgithub.com\u002Fanthropics","https:\u002F\u002Fanthropic.com","2026-11-13 03:13:59",{"source":8,"skillName":5,"commands":53,"prompt":63,"zipAvailable":64},[54,57,60],{"tool":55,"command":56},"npx","npx skills add anthropics\u002Ffinancial-services --skill earnings-preview",{"tool":58,"command":59},"bunx","bunx skills add anthropics\u002Ffinancial-services --skill earnings-preview",{"tool":61,"command":62},"pnpm","pnpm dlx skills add anthropics\u002Ffinancial-services --skill earnings-preview","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fagent-plugins\u002Fearnings-reviewer\u002Fskills\u002Fearnings-preview\u002FSKILL.md",true,[],[67,90,112,132,160,178],{"skillNo":68,"name":69,"nameZh":6,"description":70,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":71,"categories":72,"keywords":73,"publishedAt":39},"01M718K18RVV0Z7T7JR4DDYCR9","value-creation-plan","Structure post-acquisition value creation plans with revenue, cost, and operational levers mapped to an EBITDA bridge. Includes 100-day priorities, KPI targets, and accountability frameworks. Use when planning post-close execution, preparing operating partner materials, or building a board-ready value creation roadmap. Triggers on \"value creation plan\", \"100-day plan\", \"post-close plan\", \"EBITDA bridge\", \"operating plan\", or \"value creation levers\".","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fvertical-plugins\u002Fprivate-equity\u002Fskills\u002Fvalue-creation-plan\u002FSKILL.md",[],[74,75,76,77,78,79,80,81,34,82,30,83,84,29,85,86,87,25,88,89],"value","creation","value creation plan","plan","operating","ready","bridge","planning","kpi","execution","plans","roadmap","when","materials","cost","acquisition",{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":96,"publishedAt":39},"01M718JXVXRBT0736V7KDW3EHC","unit-economics","Analyze unit economics for PE targets — ARR cohorts, LTV\u002FCAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software\u002FSaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on \"unit economics\", \"cohort analysis\", \"ARR analysis\", \"LTV CAC\", \"net retention\", \"revenue quality\", or \"customer economics\".","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fvertical-plugins\u002Fprivate-equity\u002Fskills\u002Funit-economics\u002FSKILL.md",[],[97,98,99,100,101,102,37,103,30,104,29,86,105,27,106,107,108,109,110,111],"unit","economics","unit economics","cohort analysis","recurring","essential","retention","recurring revenue","saas","analyze","targets","arr","customer","revenue","cohort",{"skillNo":113,"name":114,"nameZh":6,"description":115,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":116,"categories":117,"keywords":118,"publishedAt":39},"01M718JV1463SCF8XND52PRN03","returns-analysis","Build quick IRR\u002FMOIC sensitivity tables for PE deal evaluation. Models returns across entry multiple, leverage, exit multiple, growth, and hold period scenarios. Use when sizing up a deal, stress-testing assumptions, or preparing IC returns exhibits. Triggers on \"returns analysis\", \"IRR sensitivity\", \"MOIC table\", \"what's the return at\", \"model the returns\", or \"back of the envelope\".","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fvertical-plugins\u002Fprivate-equity\u002Fskills\u002Freturns-analysis\u002FSKILL.md",[],[119,27,120,121,122,123,124,37,125,126,31,30,127,29,86,128,129,130,22,131],"returns analysis","returns","back","leverage","quick","model","sensitivity","testing","exit","growth","across","deal","models",{"skillNo":133,"name":134,"nameZh":6,"description":135,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":136,"categories":137,"keywords":146,"publishedAt":39},"01M718JRJYHENXRTAS2WES2J4E","portfolio-monitoring","Track and analyze portfolio company performance against plan. Ingests monthly\u002Fquarterly financial packages (Excel, PDF), extracts KPIs, flags variances to budget, and produces summary dashboards. Use when reviewing portfolio company financials, preparing board materials, or monitoring covenant compliance. Triggers on \"review portfolio company\", \"monthly financials\", \"how is [company] performing\", \"covenant check\", or \"portfolio update\".","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fvertical-plugins\u002Fprivate-equity\u002Fskills\u002Fportfolio-monitoring\u002FSKILL.md",[138,143],{"categoryNo":139,"categoryName":140,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":144,"categoryName":145,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000004","电子表格",[147,148,149,150,151,152,153,32,30,29,86,154,155,106,87,156,157,77,158,159],"portfolio monitoring","monitoring","portfolio","financials","PDF","xlsx","performance","review","check","packages","track","covenant","how",{"skillNo":161,"name":162,"nameZh":6,"description":163,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":164,"categories":165,"keywords":166,"publishedAt":39},"01M718JPCC86RSTX0ZH4XK26J7","ic-memo","Draft a structured investment committee memo for PE deal approval. Synthesizes due diligence findings, financial analysis, and deal terms into a professional IC-ready document. Use when preparing for investment committee, writing up a deal, or creating a formal recommendation. Triggers on \"write IC memo\", \"investment committee memo\", \"deal write-up\", \"prepare IC materials\", or \"recommendation memo\".","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fvertical-plugins\u002Fprivate-equity\u002Fskills\u002Fic-memo\u002FSKILL.md",[],[167,168,169,79,170,37,171,31,30,172,29,173,86,27,87,174,130,175,176,177],"ic memo","memo","recommendation memo","professional","recommendation","writing","document","draft","write","financial analysis","investment",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":182,"categories":183,"keywords":187,"publishedAt":39},"01M718JK2B01WZQPFHVHKY25PD","deal-sourcing","PE deal sourcing workflow — discover target companies, check CRM for existing relationships, and draft personalized founder outreach emails. Use when sourcing new deals, prospecting companies in a sector, or reaching out to founders. Triggers on \"find companies\", \"source deals\", \"draft founder email\", \"check if we've seen this company\", or \"outreach to founder\".","https:\u002F\u002Fgithub.com\u002Fanthropics\u002Ffinancial-services\u002Fblob\u002Fmain\u002Fplugins\u002Fvertical-plugins\u002Fprivate-equity\u002Fskills\u002Fdeal-sourcing\u002FSKILL.md",[184],{"categoryNo":185,"categoryName":186,"taxonomyType":141,"taxonomyTypeDesc":142},"01JBSEEDCAT000000000000005","邮件与沟通",[188,189,130,190,191,192,37,32,30,193,194,195,29,196,86,197,198,155,174,199],"sourcing","deal sourcing","target","discover","email","emails","prospecting","new","Existing","workflow","founders","find"]