[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6ADZVD39FV3G7HKHTJF7CDV":3,"skill-same:01M6ADZVD39FV3G7HKHTJF7CDV":108},{"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":28,"publishedAt":49,"linkOnly":50,"markdownContent":51,"markdownBody":52,"frontMatter":53,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":59,"ownerHtmlUrl":60,"ownerBlogUrl":61,"ownerDescription":62,"updatedAt":63,"install":64,"resources":77},"01M6ADZVD39FV3G7HKHTJF7CDV","google-analytics",null,"Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33418,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48],"analytics","google analytics","google","performance optimization","when","data-driven","traffic","about","traffic analysis","patterns","conversion","use","analyze","analysis","data","Optimization","website","metrics","performance","review","2026-11-10 10:12:30",false,"---\nname: google-analytics\ndescription: Analyze Google Analytics data, review website performance metrics, identify traffic patterns, and suggest data-driven improvements. Use when the user asks about analytics, website metrics, traffic analysis, conversion rates, user behavior, or performance optimization.\n---\n\n# Google Analytics Analysis\n\nAnalyze website performance using Google Analytics data to provide actionable insights and improvement recommendations.\n\n## Quick Start\n\n### 1. Setup Authentication\n\nThis Skill requires Google Analytics API credentials. Set up environment variables:\n\n```bash\nexport GOOGLE_ANALYTICS_PROPERTY_ID=\"your-property-id\"\nexport GOOGLE_APPLICATION_CREDENTIALS=\"\u002Fpath\u002Fto\u002Fservice-account-key.json\"\n```\n\nOr create a `.env` file in your project root:\n\n```env\nGOOGLE_ANALYTICS_PROPERTY_ID=123456789\nGOOGLE_APPLICATION_CREDENTIALS=\u002Fpath\u002Fto\u002Fservice-account-key.json\n```\n\n**Never commit credentials to version control.** The service account JSON file should be stored securely outside your repository.\n\n### 2. Install Required Packages\n\n```bash\n# Option 1: Install from requirements file (recommended)\npip install -r cli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002Frequirements.txt\n\n# Option 2: Install individually\npip install google-analytics-data python-dotenv pandas\n```\n\n### 3. Analyze Your Project\n\nOnce configured, I can:\n- Review current traffic and user behavior metrics\n- Identify top-performing and underperforming pages\n- Analyze traffic sources and conversion funnels\n- Compare performance across time periods\n- Suggest data-driven improvements\n\n## How to Use\n\nAsk me questions like:\n- \"Review our Google Analytics performance for the last 30 days\"\n- \"What are our top traffic sources?\"\n- \"Which pages have the highest bounce rates?\"\n- \"Analyze user engagement and suggest improvements\"\n- \"Compare this month's performance to last month\"\n\n## Analysis Workflow\n\nWhen you ask me to analyze Google Analytics data, I will:\n\n1. **Connect to the API** using the helper script\n2. **Fetch relevant metrics** based on your question\n3. **Analyze the data** looking for:\n   - Traffic trends and patterns\n   - User behavior insights\n   - Performance bottlenecks\n   - Conversion opportunities\n4. **Provide recommendations** with:\n   - Specific improvement suggestions\n   - Priority level (high\u002Fmedium\u002Flow)\n   - Expected impact\n   - Implementation guidance\n\n## Common Metrics\n\nFor detailed metric definitions and dimensions, see [REFERENCE.md](REFERENCE.md).\n\n### Traffic Metrics\n- Sessions, Users, New Users\n- Page views, Screens per Session\n- Average Session Duration\n\n### Engagement Metrics\n- Bounce Rate, Engagement Rate\n- Event Count, Conversions\n- Scroll Depth, Click-through Rate\n\n### Acquisition Metrics\n- Traffic Source\u002FMedium\n- Campaign Performance\n- Channel Grouping\n\n### Conversion Metrics\n- Goal Completions\n- E-commerce Transactions\n- Conversion Rate by Source\n\n## Analysis Examples\n\nFor complete analysis patterns and use cases, see [EXAMPLES.md](EXAMPLES.md).\n\n## Scripts\n\nThe Skill includes utility scripts for API interaction:\n\n### Fetch Current Performance\n```bash\npython scripts\u002Fga_client.py --days 30 --metrics sessions,users,bounceRate\n```\n\n### Analyze and Generate Report\n```bash\npython scripts\u002Fanalyze.py --period last-30-days --compare previous-period\n```\n\nThe scripts handle API authentication, data fetching, and basic analysis. I'll interpret the results and provide actionable recommendations.\n\n## Troubleshooting\n\n**Authentication Error**: Verify that:\n- `GOOGLE_APPLICATION_CREDENTIALS` points to a valid service account JSON file\n- The service account has \"Viewer\" access to your GA4 property\n- `GOOGLE_ANALYTICS_PROPERTY_ID` matches your GA4 property ID (not the measurement ID)\n\n**No Data Returned**: Check that:\n- The property ID is correct (find it in GA4 Admin > Property Settings)\n- The date range contains data\n- The service account has been granted access in GA4\n\n**Import Errors**: Install required packages:\n```bash\npip install google-analytics-data python-dotenv pandas\n```\n\n## Security Notes\n\n- **Never hardcode** API credentials or property IDs in code\n- Store service account JSON files **outside** version control\n- Use environment variables or `.env` files for configuration\n- Add `.env` and credential files to `.gitignore`\n- Rotate service account keys periodically\n- Use least-privilege access (Viewer role only)\n\n## Data Privacy\n\nThis Skill accesses aggregated analytics data only. It does not:\n- Access personally identifiable information (PII)\n- Store analytics data persistently\n- Share data with external services\n- Modify your Google Analytics configuration\n\nAll data is processed locally and used only to generate recommendations during the conversation.\n","# Google Analytics Analysis\n\nAnalyze website performance using Google Analytics data to provide actionable insights and improvement recommendations.\n\n## Quick Start\n\n### 1. Setup Authentication\n\nThis Skill requires Google Analytics API credentials. Set up environment variables:\n\n```bash\nexport GOOGLE_ANALYTICS_PROPERTY_ID=\"your-property-id\"\nexport GOOGLE_APPLICATION_CREDENTIALS=\"\u002Fpath\u002Fto\u002Fservice-account-key.json\"\n```\n\nOr create a `.env` file in your project root:\n\n```env\nGOOGLE_ANALYTICS_PROPERTY_ID=123456789\nGOOGLE_APPLICATION_CREDENTIALS=\u002Fpath\u002Fto\u002Fservice-account-key.json\n```\n\n**Never commit credentials to version control.** The service account JSON file should be stored securely outside your repository.\n\n### 2. Install Required Packages\n\n```bash\n# Option 1: Install from requirements file (recommended)\npip install -r cli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002Frequirements.txt\n\n# Option 2: Install individually\npip install google-analytics-data python-dotenv pandas\n```\n\n### 3. Analyze Your Project\n\nOnce configured, I can:\n- Review current traffic and user behavior metrics\n- Identify top-performing and underperforming pages\n- Analyze traffic sources and conversion funnels\n- Compare performance across time periods\n- Suggest data-driven improvements\n\n## How to Use\n\nAsk me questions like:\n- \"Review our Google Analytics performance for the last 30 days\"\n- \"What are our top traffic sources?\"\n- \"Which pages have the highest bounce rates?\"\n- \"Analyze user engagement and suggest improvements\"\n- \"Compare this month's performance to last month\"\n\n## Analysis Workflow\n\nWhen you ask me to analyze Google Analytics data, I will:\n\n1. **Connect to the API** using the helper script\n2. **Fetch relevant metrics** based on your question\n3. **Analyze the data** looking for:\n   - Traffic trends and patterns\n   - User behavior insights\n   - Performance bottlenecks\n   - Conversion opportunities\n4. **Provide recommendations** with:\n   - Specific improvement suggestions\n   - Priority level (high\u002Fmedium\u002Flow)\n   - Expected impact\n   - Implementation guidance\n\n## Common Metrics\n\nFor detailed metric definitions and dimensions, see [REFERENCE.md](REFERENCE.md).\n\n### Traffic Metrics\n- Sessions, Users, New Users\n- Page views, Screens per Session\n- Average Session Duration\n\n### Engagement Metrics\n- Bounce Rate, Engagement Rate\n- Event Count, Conversions\n- Scroll Depth, Click-through Rate\n\n### Acquisition Metrics\n- Traffic Source\u002FMedium\n- Campaign Performance\n- Channel Grouping\n\n### Conversion Metrics\n- Goal Completions\n- E-commerce Transactions\n- Conversion Rate by Source\n\n## Analysis Examples\n\nFor complete analysis patterns and use cases, see [EXAMPLES.md](EXAMPLES.md).\n\n## Scripts\n\nThe Skill includes utility scripts for API interaction:\n\n### Fetch Current Performance\n```bash\npython scripts\u002Fga_client.py --days 30 --metrics sessions,users,bounceRate\n```\n\n### Analyze and Generate Report\n```bash\npython scripts\u002Fanalyze.py --period last-30-days --compare previous-period\n```\n\nThe scripts handle API authentication, data fetching, and basic analysis. I'll interpret the results and provide actionable recommendations.\n\n## Troubleshooting\n\n**Authentication Error**: Verify that:\n- `GOOGLE_APPLICATION_CREDENTIALS` points to a valid service account JSON file\n- The service account has \"Viewer\" access to your GA4 property\n- `GOOGLE_ANALYTICS_PROPERTY_ID` matches your GA4 property ID (not the measurement ID)\n\n**No Data Returned**: Check that:\n- The property ID is correct (find it in GA4 Admin > Property Settings)\n- The date range contains data\n- The service account has been granted access in GA4\n\n**Import Errors**: Install required packages:\n```bash\npip install google-analytics-data python-dotenv pandas\n```\n\n## Security Notes\n\n- **Never hardcode** API credentials or property IDs in code\n- Store service account JSON files **outside** version control\n- Use environment variables or `.env` files for configuration\n- Add `.env` and credential files to `.gitignore`\n- Rotate service account keys periodically\n- Use least-privilege access (Viewer role only)\n\n## Data Privacy\n\nThis Skill accesses aggregated analytics data only. It does not:\n- Access personally identifiable information (PII)\n- Store analytics data persistently\n- Share data with external services\n- Modify your Google Analytics configuration\n\nAll data is processed locally and used only to generate recommendations during the conversation.\n",{"name":5,"description":7},"main","2b749c82b5d11fac39d9a6e021ce3f5b8a541bd1","cli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics",3926,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates","https:\u002F\u002Faitmpl.com","https:\u002F\u002Fgithub.com\u002Fdavila7","https:\u002F\u002Fdanielavila.me","Building AI dev tools with LLMs","2026-11-12 14:45:56",{"source":8,"skillName":5,"commands":65,"prompt":75,"zipAvailable":76},[66,69,72],{"tool":67,"command":68},"npx","npx skills add davila7\u002Fclaude-code-templates --skill google-analytics",{"tool":70,"command":71},"bunx","bunx skills add davila7\u002Fclaude-code-templates --skill google-analytics",{"tool":73,"command":74},"pnpm","pnpm dlx skills add davila7\u002Fclaude-code-templates --skill google-analytics","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002FSKILL.md",true,[78,84,90,94,98,104],{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},".env.example","OTHER","其他",1153,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002F.env.example",{"path":85,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"EXAMPLES.md","REFERENCE","参考文档",13867,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002FEXAMPLES.md",{"path":91,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":92,"sourceHtmlUrl":93},"REFERENCE.md",8853,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002FREFERENCE.md",{"path":95,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":96,"sourceHtmlUrl":97},"requirements.txt",152,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002Frequirements.txt",{"path":99,"resourceType":100,"resourceTypeDesc":101,"sizeBytes":102,"sourceHtmlUrl":103},"scripts\u002Fanalyze.py","SCRIPT","脚本",15777,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002Fscripts\u002Fanalyze.py",{"path":105,"resourceType":100,"resourceTypeDesc":101,"sizeBytes":106,"sourceHtmlUrl":107},"scripts\u002Fga_client.py",11325,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fanalytics\u002Fgoogle-analytics\u002Fscripts\u002Fga_client.py",[109,137,164,193,228,252],{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":113,"categories":114,"keywords":118,"publishedAt":49},"01M70NHBTQ8BV0A2SCAZXEPHCX","wealthville-pool-scoring","Score DeFi liquidity pools before providing liquidity. Returns a 0-100 pool score and an Enter\u002FHold\u002FExit\u002FReduce\u002FAvoid verdict with calibrated confidence for ~68,800 Solana pools and 575 EVM pools, plus a public miss-inclusive track record. Use when asked whether a pool is worth LPing into, which pools look best right now, or how accurate the scores have actually been.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fweb-data\u002Fwealthville-pool-scoring\u002FSKILL.md",[115],{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[119,120,121,122,123,124,125,126,40,33,127,128,129,130,131,132,133,134,135,136],"scoring","pool","wealthville pool scoring","liquidity","which","for","exit","now","reduce","with","record","track","verdict","evm","solana","how","public","look",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":144,"publishedAt":49},"01M70MB6VR8ERJ4EM8D5KHBMEV","technical-debt-auditor","Scans a codebase and produces a quantified technical debt report with a prioritized remediation plan. Analyzes dead code, TODO\u002FFIXME\u002FHACK markers, dependency staleness, complexity hotspots, code duplication signals, test coverage gaps, unused exports, and outdated patterns. Use this skill when the user asks to audit their codebase for tech debt, wants a health check of their code quality, says things like \"where should I focus refactoring\", \"find code smells\", \"audit my codebase\", \"what technical debt do we have\", \"prioritize cleanup work\", or asks about code quality metrics. Also trigger when the user mentions \"code rot\", \"legacy cleanup\", \"refactoring priorities\", or wants to understand the overall health of a project before a major effort. Trigger even if the user doesn't say \"technical debt\" explicitly — any request to systematically assess code quality and identify improvement priorities belongs here.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Ftechnical-debt-auditor\u002FSKILL.md",[143],{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},[145,146,147,148,149,150,151,152,153,154,155,33,156,157,158,159,160,161,162,163],"technical debt","debt","technical","technical debt auditor","auditor","coverage","complexity","markers","project","cleanup","unused","code","todo","work","plan","focus","signals","audit","dependency",{"skillNo":165,"name":166,"nameZh":6,"description":167,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":168,"categories":169,"keywords":175,"publishedAt":49},"01M70KPYH9QNHCNME5GJQGE22K","readonly-sql-guard","Make an agent's database access provably read-only. Use when an agent runs caller-supplied SQL against a production\u002FERP\u002Fanalytics database (a \"query\" MCP tool, text-to-SQL, an admin console), or when reviewing DB-access code for write\u002FDDL\u002Fside-effect\u002Ftransaction-escape risks. Checks what a statement CALLS, not just its shape.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdatabase\u002Freadonly-sql-guard\u002FSKILL.md",[170,173,174],{"categoryNo":171,"categoryName":172,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":26,"taxonomyTypeDesc":27},[176,177,178,179,180,181,182,124,183,184,185,186,187,188,189,40,190,191,33,192],"readonly","guard","sql guard","sql","readonly sql guard","erp","effect","read-only","db","just","tool","calls","only","MCP","access","database","query",{"skillNo":194,"name":195,"nameZh":6,"description":196,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":197,"licenseFileUrl":198,"sourceHtmlUrl":199,"categories":200,"keywords":204,"publishedAt":49},"01M6AFY6F7CC2BBZP1QD6VTNVC","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.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[201],{"categoryNo":202,"categoryName":203,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",[205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,124,227],"artifacts builder","web","web artifacts builder","artifacts","builder","state","routing","state management","component","css","frontend","ui","Tools","file","components","shadcn","react","Tailwind","suite","jsx","html","single-file","ui components",{"skillNo":229,"name":230,"nameZh":6,"description":231,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":197,"licenseFileUrl":232,"sourceHtmlUrl":233,"categories":234,"keywords":239,"publishedAt":49},"01M6AFWF33SFV9Z3SF4PEEE4BF","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.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FSKILL.md",[235,238],{"categoryNo":236,"categoryName":237,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":202,"categoryName":203,"taxonomyType":21,"taxonomyTypeDesc":22},[240,241,242,243,244,206,245,215,216,246,247,248,249,124,250,128,251],"webapp testing","testing","webapp","browser","playwright","applications","debugging","toolkit","logs","screenshots","local","behavior",{"skillNo":253,"name":254,"nameZh":6,"description":255,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":197,"licenseFileUrl":256,"sourceHtmlUrl":257,"categories":258,"keywords":266,"publishedAt":49},"01M6AF67Q67JJJ5V51JR2P52KA","discernment-nudge","After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FSKILL.md",[259,262,263],{"categoryNo":260,"categoryName":261,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":116,"categoryName":117,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":264,"categoryName":265,"taxonomyType":26,"taxonomyTypeDesc":27},"01JBSEEDCAT000000000000036","内容创作者",[267,268,269,270,271,272,43,273,208,274,218,156,275,48,276,277,278,188,279,33,280,42,281,282,283,134,284],"discernment nudge","nudge","interpretation","help","run","reasoning","writing","lookup","content","conversation","short","up","invoke","you","claims","argument","assemble","recommendations"]