[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FH9WPYB3TWT09J90NHKCJ":3,"skill-same:01M71FH9WPYB3TWT09J90NHKCJ":101},{"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":49,"commitSha":50,"skillDirectory":51,"forksCount":14,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":54,"ownerDescription":55,"updatedAt":56,"install":57,"resources":70},"01M71FH9WPYB3TWT09J90NHKCJ","saas-metrics-coach",null,"SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how their SaaS business is doing.","agency-black\u002FSkills","agency-black","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F234862658?v=4","01M6HWVFPNGNR5N2CX9ECSAD57","agencia.black","01M719WF77BF3HN0N9FK1APEFY",0,"MIT","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"metrics","saas","saas metrics coach","saas metrics","coach","ltv","customer","mrr","2026","when","churn","revenue","advisor","use","nrr","arr","business","financial health","how","health","2026-11-10 10:12:30",false,"---\nname: saas-metrics-coach\ndescription: SaaS financial health advisor. Use when a user shares revenue or customer numbers, or mentions ARR, MRR, churn, LTV, CAC, NRR, or asks how their SaaS business is doing.\nlicense: MIT\nmetadata:\n  version: 1.0.0\n  author: Abbas Mir\n  category: finance\n  updated: 2026-03-08\n---\n\n# SaaS Metrics Coach\n\nAct as a senior SaaS CFO advisor. Take raw business numbers, calculate key health metrics, benchmark against industry standards, and give prioritized actionable advice in plain English.\n\n## Step 1 — Collect Inputs\n\nIf not already provided, ask for these in a single grouped request:\n\n- Revenue: current MRR, MRR last month, expansion MRR, churned MRR\n- Customers: total active, new this month, churned this month\n- Costs: sales and marketing spend, gross margin %\n\nWork with partial data. Be explicit about what is missing and what assumptions are being made.\n\n## Step 2 — Calculate Metrics\n\nRun `scripts\u002Fmetrics_calculator.py` with the user's inputs. If the script is unavailable, use the formulas in `references\u002Fformulas.md`.\n\nAlways attempt to compute: ARR, MRR growth %, monthly churn rate, CAC, LTV, LTV:CAC ratio, CAC payback period, NRR.\n\n**Additional Analysis Tools:**\n- Use `scripts\u002Fquick_ratio_calculator.py` when expansion\u002Fchurn MRR data is available\n- Use `scripts\u002Funit_economics_simulator.py` for forward-looking projections\n\n## Step 3 — Benchmark Each Metric\n\nLoad `references\u002Fbenchmarks.md`. For each metric show:\n- The calculated value\n- The relevant benchmark range for the user's segment and stage\n- A plain status label: HEALTHY \u002F WATCH \u002F CRITICAL\n\nMatch the benchmark tier to the user's market segment (Enterprise \u002F Mid-Market \u002F SMB \u002F PLG) and company stage (Early \u002F Growth \u002F Scale). Ask if unclear.\n\n## Step 4 — Prioritize and Recommend\n\nIdentify the top 2-3 metrics at WATCH or CRITICAL status. For each one state:\n- What is happening (one sentence, plain English)\n- Why it matters to the business\n- Two or three specific actions to take this month\n\nOrder by impact — address the most damaging problem first.\n\n## Step 5 — Output Format\n\nAlways use this exact structure:\n\n```\n# SaaS Health Report — [Month Year]\n\n## Metrics at a Glance\n| Metric | Your Value | Benchmark | Status |\n|--------|------------|-----------|--------|\n\n## Overall Picture\n[2-3 sentences, plain English summary]\n\n## Priority Issues\n\n### 1. [Metric Name]\nWhat is happening: ...\nWhy it matters: ...\nFix it this month: ...\n\n### 2. [Metric Name]\n...\n\n## What is Working\n[1-2 genuine strengths, no padding]\n\n## 90-Day Focus\n[Single metric to move + specific numeric target]\n```\n\n## Examples\n\n**Example 1 — Partial data**\n\nInput: \"MRR is $80k, we have 200 customers, about 3 cancel each month.\"\n\nExpected output: Calculates ARPA ($400), monthly churn (1.5%), ARR ($960k), LTV estimate. Flags CAC and growth rate as missing. Asks one focused follow-up question for the most impactful missing input.\n\n**Example 2 — Critical scenario**\n\nInput: \"MRR $22k (was $23.5k), 80 customers, lost 9, gained 6, spent $15k on ads, 65% gross margin.\"\n\nExpected output: Flags negative MoM growth (-6.4%), critical churn (11.25%), and LTV:CAC of 0.64:1 as CRITICAL. Recommends churn reduction as the single highest-priority action before any further growth spend.\n\n## Key Principles\n\n- Be direct. If a metric is bad, say it is bad.\n- Explain every metric in one sentence before showing the number.\n- Cap priority issues at three. More than three paralyzes action.\n- Context changes benchmarks. Five percent churn is catastrophic for Enterprise SaaS but normal for SMB\u002FPLG. Always confirm the user's target market before scoring.\n\n## Reference Files\n\n- `references\u002Fformulas.md` — All metric formulas with worked examples\n- `references\u002Fbenchmarks.md` — Industry benchmark ranges by stage and segment\n- `assets\u002Finput-template.md` — Blank input form to share with users\n- `scripts\u002Fmetrics_calculator.py` — Core metrics calculator (ARR, MRR, churn, CAC, LTV, NRR)\n- `scripts\u002Fquick_ratio_calculator.py` — Growth efficiency metric (Quick Ratio)\n- `scripts\u002Funit_economics_simulator.py` — 12-month forward projection\n\n## Tools\n\n### 1. Metrics Calculator (`scripts\u002Fmetrics_calculator.py`)\nCore SaaS metrics from raw business numbers.\n\n```bash\n# Interactive mode\npython scripts\u002Fmetrics_calculator.py\n\n# CLI mode\npython scripts\u002Fmetrics_calculator.py --mrr 50000 --customers 100 --churned 5 --json\n```\n\n### 2. Quick Ratio Calculator (`scripts\u002Fquick_ratio_calculator.py`)\nGrowth efficiency metric: (New MRR + Expansion) \u002F (Churned + Contraction)\n\n```bash\npython scripts\u002Fquick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --contraction 500\npython scripts\u002Fquick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --json\n```\n\n**Benchmarks:**\n- \u003C 1.0 = CRITICAL (losing faster than gaining)\n- 1-2 = WATCH (marginal growth)\n- 2-4 = HEALTHY (good efficiency)\n- \\> 4 = EXCELLENT (strong growth)\n\n### 3. Unit Economics Simulator (`scripts\u002Funit_economics_simulator.py`)\nProject metrics forward 12 months based on growth\u002Fchurn assumptions.\n\n```bash\npython scripts\u002Funit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000\npython scripts\u002Funit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000 --json\n```\n\n**Use for:**\n- \"What if we grow at X% per month?\"\n- Runway projections\n- Scenario planning (best\u002Fbase\u002Fworst case)\n\n## Related Skills\n\n- **financial-analyst**: Use for DCF valuation, budget variance analysis, and traditional financial modeling. NOT for SaaS-specific metrics like CAC, LTV, or churn.\n- **business-growth\u002Fcustomer-success**: Use for retention strategies and customer health scoring. Complements this skill when churn is flagged as CRITICAL.\n","# SaaS Metrics Coach\n\nAct as a senior SaaS CFO advisor. Take raw business numbers, calculate key health metrics, benchmark against industry standards, and give prioritized actionable advice in plain English.\n\n## Step 1 — Collect Inputs\n\nIf not already provided, ask for these in a single grouped request:\n\n- Revenue: current MRR, MRR last month, expansion MRR, churned MRR\n- Customers: total active, new this month, churned this month\n- Costs: sales and marketing spend, gross margin %\n\nWork with partial data. Be explicit about what is missing and what assumptions are being made.\n\n## Step 2 — Calculate Metrics\n\nRun `scripts\u002Fmetrics_calculator.py` with the user's inputs. If the script is unavailable, use the formulas in `references\u002Fformulas.md`.\n\nAlways attempt to compute: ARR, MRR growth %, monthly churn rate, CAC, LTV, LTV:CAC ratio, CAC payback period, NRR.\n\n**Additional Analysis Tools:**\n- Use `scripts\u002Fquick_ratio_calculator.py` when expansion\u002Fchurn MRR data is available\n- Use `scripts\u002Funit_economics_simulator.py` for forward-looking projections\n\n## Step 3 — Benchmark Each Metric\n\nLoad `references\u002Fbenchmarks.md`. For each metric show:\n- The calculated value\n- The relevant benchmark range for the user's segment and stage\n- A plain status label: HEALTHY \u002F WATCH \u002F CRITICAL\n\nMatch the benchmark tier to the user's market segment (Enterprise \u002F Mid-Market \u002F SMB \u002F PLG) and company stage (Early \u002F Growth \u002F Scale). Ask if unclear.\n\n## Step 4 — Prioritize and Recommend\n\nIdentify the top 2-3 metrics at WATCH or CRITICAL status. For each one state:\n- What is happening (one sentence, plain English)\n- Why it matters to the business\n- Two or three specific actions to take this month\n\nOrder by impact — address the most damaging problem first.\n\n## Step 5 — Output Format\n\nAlways use this exact structure:\n\n```\n# SaaS Health Report — [Month Year]\n\n## Metrics at a Glance\n| Metric | Your Value | Benchmark | Status |\n|--------|------------|-----------|--------|\n\n## Overall Picture\n[2-3 sentences, plain English summary]\n\n## Priority Issues\n\n### 1. [Metric Name]\nWhat is happening: ...\nWhy it matters: ...\nFix it this month: ...\n\n### 2. [Metric Name]\n...\n\n## What is Working\n[1-2 genuine strengths, no padding]\n\n## 90-Day Focus\n[Single metric to move + specific numeric target]\n```\n\n## Examples\n\n**Example 1 — Partial data**\n\nInput: \"MRR is $80k, we have 200 customers, about 3 cancel each month.\"\n\nExpected output: Calculates ARPA ($400), monthly churn (1.5%), ARR ($960k), LTV estimate. Flags CAC and growth rate as missing. Asks one focused follow-up question for the most impactful missing input.\n\n**Example 2 — Critical scenario**\n\nInput: \"MRR $22k (was $23.5k), 80 customers, lost 9, gained 6, spent $15k on ads, 65% gross margin.\"\n\nExpected output: Flags negative MoM growth (-6.4%), critical churn (11.25%), and LTV:CAC of 0.64:1 as CRITICAL. Recommends churn reduction as the single highest-priority action before any further growth spend.\n\n## Key Principles\n\n- Be direct. If a metric is bad, say it is bad.\n- Explain every metric in one sentence before showing the number.\n- Cap priority issues at three. More than three paralyzes action.\n- Context changes benchmarks. Five percent churn is catastrophic for Enterprise SaaS but normal for SMB\u002FPLG. Always confirm the user's target market before scoring.\n\n## Reference Files\n\n- `references\u002Fformulas.md` — All metric formulas with worked examples\n- `references\u002Fbenchmarks.md` — Industry benchmark ranges by stage and segment\n- `assets\u002Finput-template.md` — Blank input form to share with users\n- `scripts\u002Fmetrics_calculator.py` — Core metrics calculator (ARR, MRR, churn, CAC, LTV, NRR)\n- `scripts\u002Fquick_ratio_calculator.py` — Growth efficiency metric (Quick Ratio)\n- `scripts\u002Funit_economics_simulator.py` — 12-month forward projection\n\n## Tools\n\n### 1. Metrics Calculator (`scripts\u002Fmetrics_calculator.py`)\nCore SaaS metrics from raw business numbers.\n\n```bash\n# Interactive mode\npython scripts\u002Fmetrics_calculator.py\n\n# CLI mode\npython scripts\u002Fmetrics_calculator.py --mrr 50000 --customers 100 --churned 5 --json\n```\n\n### 2. Quick Ratio Calculator (`scripts\u002Fquick_ratio_calculator.py`)\nGrowth efficiency metric: (New MRR + Expansion) \u002F (Churned + Contraction)\n\n```bash\npython scripts\u002Fquick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --contraction 500\npython scripts\u002Fquick_ratio_calculator.py --new-mrr 10000 --expansion 2000 --churned 3000 --json\n```\n\n**Benchmarks:**\n- \u003C 1.0 = CRITICAL (losing faster than gaining)\n- 1-2 = WATCH (marginal growth)\n- 2-4 = HEALTHY (good efficiency)\n- \\> 4 = EXCELLENT (strong growth)\n\n### 3. Unit Economics Simulator (`scripts\u002Funit_economics_simulator.py`)\nProject metrics forward 12 months based on growth\u002Fchurn assumptions.\n\n```bash\npython scripts\u002Funit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000\npython scripts\u002Funit_economics_simulator.py --mrr 50000 --growth 10 --churn 3 --cac 2000 --json\n```\n\n**Use for:**\n- \"What if we grow at X% per month?\"\n- Runway projections\n- Scenario planning (best\u002Fbase\u002Fworst case)\n\n## Related Skills\n\n- **financial-analyst**: Use for DCF valuation, budget variance analysis, and traditional financial modeling. NOT for SaaS-specific metrics like CAC, LTV, or churn.\n- **business-growth\u002Fcustomer-success**: Use for retention strategies and customer health scoring. Complements this skill when churn is flagged as CRITICAL.\n",{"name":5,"license":15,"metadata":44,"description":7},{"author":45,"updated":46,"version":47,"category":48},"Abbas Mir",1772928000000,"1.0.0","finance","main","681496e0662f4c45c4758fae9d4510ae87311bf2","finance\u002Fskills\u002Fsaas-metrics-coach","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills","https:\u002F\u002Fgithub.com\u002Fagency-black","http:\u002F\u002Fwww.dogma.black","Las grandes ideas merecen una ejecución impecable. Construimos plataformas web, aplicaciones y ecosistemas digitales completos. Esta Trinidad es nuestro dogma.","2026-05-29 16:13:55",{"source":8,"skillName":5,"commands":58,"prompt":68,"zipAvailable":69},[59,62,65],{"tool":60,"command":61},"npx","npx skills add agency-black\u002FSkills --skill saas-metrics-coach",{"tool":63,"command":64},"bunx","bunx skills add agency-black\u002FSkills --skill saas-metrics-coach",{"tool":66,"command":67},"pnpm","pnpm dlx skills add agency-black\u002FSkills --skill saas-metrics-coach","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002FSKILL.md",true,[71,77,83,87,93,97],{"path":72,"resourceType":73,"resourceTypeDesc":74,"sizeBytes":75,"sourceHtmlUrl":76},"assets\u002Finput-template.md","ASSET","资产文件",718,"https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002Fassets\u002Finput-template.md",{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"references\u002Fbenchmarks.md","REFERENCE","参考文档",2530,"https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002Freferences\u002Fbenchmarks.md",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002Fformulas.md",2493,"https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002Freferences\u002Fformulas.md",{"path":88,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":91,"sourceHtmlUrl":92},"scripts\u002Fmetrics_calculator.py","SCRIPT","脚本",9733,"https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002Fscripts\u002Fmetrics_calculator.py",{"path":94,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":95,"sourceHtmlUrl":96},"scripts\u002Fquick_ratio_calculator.py",6142,"https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002Fscripts\u002Fquick_ratio_calculator.py",{"path":98,"resourceType":89,"resourceTypeDesc":90,"sizeBytes":99,"sourceHtmlUrl":100},"scripts\u002Funit_economics_simulator.py",7105,"https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Ffinance\u002Fskills\u002Fsaas-metrics-coach\u002Fscripts\u002Funit_economics_simulator.py",[102,128,158,188,213,237],{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":108,"publishedAt":39},"01M71JZVZ0TVW7Z5DQBRWSBG8A","zarr-python","Chunked N-D arrays for cloud storage (Zarr-Python 3). Compressed arrays, parallel I\u002FO, S3\u002FGCS via fsspec, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fzarr-python\u002FSKILL.md",[],[109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,32,124,125,126,127],"zarr python","python","zarr","arrays","Cloud Storage","remote","workflows","scientific","read","write","edit","parallel","dask","for","s3fs","numpy","s3","scientific computing","scale",{"skillNo":129,"name":130,"nameZh":6,"description":131,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":132,"sourceHtmlUrl":133,"categories":134,"keywords":140,"publishedAt":39},"01M71JYXC5VAEJT8KXN5GRK32S","xvary-stock-research","Thesis-driven equity analysis from public SEC EDGAR and market data; \u002Fanalyze, \u002Fscore, \u002Fcompare workflows with bundled Python tools (Claude Code, Cursor, Codex).","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fxvary-stock-research\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fxvary-stock-research\u002FSKILL.md",[135],{"categoryNo":136,"categoryName":137,"taxonomyType":138,"taxonomyTypeDesc":139},"01JBSEEDCAT000000000000021","资料检索与研究","SCENARIO","使用场景",[141,142,143,144,145,146,147,110,148,115,149,150,151,152,153,154,155,156,157,27],"xvary","stock","research","xvary stock research","sec edgar","community","equity","thesis","analysis","code","Market","compare","market data","analyze","with","codex","cursor",{"skillNo":159,"name":160,"nameZh":6,"description":161,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":162,"licenseFileUrl":163,"sourceHtmlUrl":164,"categories":165,"keywords":172,"publishedAt":39},"01M71JVSDPDQ5040YBN6J1ASKY","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fwebapp-testing\u002FSKILL.md",[166,169],{"categoryNo":167,"categoryName":168,"taxonomyType":138,"taxonomyTypeDesc":139},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":170,"categoryName":171,"taxonomyType":138,"taxonomyTypeDesc":139},"01JBSEEDCAT000000000000009","前端开发",[173,174,175,122,176,177,178,179,180,181,182,155,183,184,185,186,187],"webapp","testing","webapp testing","applications","local","frontend","debugging","toolkit","logs","browser","playwright","web","behavior","ui","screenshots",{"skillNo":189,"name":190,"nameZh":6,"description":191,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":162,"licenseFileUrl":192,"sourceHtmlUrl":193,"categories":194,"keywords":196,"publishedAt":39},"01M71JV64CW7R6FYYK9JWWGW0X","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fweb-artifacts-builder\u002FSKILL.md",[195],{"categoryNo":170,"categoryName":171,"taxonomyType":138,"taxonomyTypeDesc":139},[197,198,199,184,200,201,202,122,203,204,178,205,32,206,207,208,209,210,211,212],"builder","artifacts builder","artifacts","web artifacts builder","single-file","css","Tailwind","ui components","single","file","components","react","multi","state","routing","state management",{"skillNo":214,"name":215,"nameZh":6,"description":216,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":217,"categories":218,"keywords":220,"publishedAt":39},"01M71JS4X2FRY41DE84DEP06MN","vercel-react-view-transitions","Guide for implementing smooth, native-feeling animations using React's View Transition API (`\u003CViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter\u002Fexit of components, animate list reorder, implement directional (forward\u002Fback) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-view-transitions\u002FSKILL.md",[219],{"categoryNo":170,"categoryName":171,"taxonomyType":138,"taxonomyTypeDesc":139},[208,221,222,223,224,225,226,227,228,202,229,230,231,232,28,207,233,234,235,236],"vercel react view transitions","view","react view transitions","vercel","transitions","shared","back","Animation","types","states","element","implementing","api","route","create","libraries",{"skillNo":238,"name":239,"nameZh":6,"description":240,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":241,"categories":242,"keywords":244,"publishedAt":39},"01M71JS1WZ1J4F9YVC2203JBJW","vercel-react-native-skills","React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-native-skills\u002FSKILL.md",[243],{"categoryNo":170,"categoryName":171,"taxonomyType":138,"taxonomyTypeDesc":139},[224,245,208,246,247,248,249,250,251,122,252,232,253,32,254,255,28,256,257,207],"vercel react native skills","react native","native","react native skills","modules","platform","animations","performance","triggers","react native components","apps","best practices","tasks"]