[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AF7S0D49F48NBDG9G4RTRY":3,"skill-same:01M6AF7S0D49F48NBDG9G4RTRY":68},{"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":31,"linkOnly":32,"markdownContent":33,"markdownBody":34,"frontMatter":35,"refName":38,"commitSha":39,"skillDirectory":40,"forksCount":41,"repositoryHtmlUrl":42,"repositoryHomepageUrl":43,"ownerHtmlUrl":44,"ownerBlogUrl":45,"ownerDescription":46,"updatedAt":47,"install":48,"resources":61},"01M6AF7S0D49F48NBDG9G4RTRY","performance-optimizer",null,"Identifies and fixes performance bottlenecks in code, databases, and APIs. Measures before and after to prove improvements.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33286,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fperformance-optimizer\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30],"performance","performance optimizer","optimizer","safe","development","code","before and after","databases","community","fixes","prove","2026","2026-11-10 10:12:30",false,"---\nname: performance-optimizer\ndescription: \"Identifies and fixes performance bottlenecks in code, databases, and APIs. Measures before and after to prove improvements.\"\nmetadata:\n  category: development\n  risk: safe\n  source: community\n  date_added: \"2026-03-05\"\n---\n\n# Performance Optimizer\n\nFind and fix performance bottlenecks. Measure, optimize, verify. Make it fast.\n\n## When to Use This Skill\n\n- App is slow or laggy\n- User complains about performance\n- Page load times are high\n- API responses are slow\n- Database queries take too long\n- User mentions \"slow\", \"lag\", \"performance\", or \"optimize\"\n\n## The Optimization Process\n\n### 1. Measure First\n\nNever optimize without measuring:\n\n```javascript\n\u002F\u002F Measure execution time\nconsole.time('operation');\nawait slowOperation();\nconsole.timeEnd('operation'); \u002F\u002F operation: 2341ms\n```\n\n**What to measure:**\n- Page load time\n- API response time\n- Database query time\n- Function execution time\n- Memory usage\n- Network requests\n\n### 2. Find the Bottleneck\n\nUse profiling tools to find the slow parts:\n\n**Browser:**\n```\nDevTools → Performance tab → Record → Stop\nLook for long tasks (red bars)\n```\n\n**Node.js:**\n```bash\nnode --prof app.js\nnode --prof-process isolate-*.log > profile.txt\n```\n\n**Database:**\n```sql\nEXPLAIN ANALYZE SELECT * FROM users WHERE email = 'test@example.com';\n```\n\n### 3. Optimize\n\nFix the slowest thing first (biggest impact).\n\n## Common Optimizations\n\n### Database Queries\n\n**Problem: N+1 Queries**\n```javascript\n\u002F\u002F Bad: N+1 queries\nconst users = await db.users.find();\nfor (const user of users) {\n  user.posts = await db.posts.find({ userId: user.id }); \u002F\u002F N queries\n}\n\n\u002F\u002F Good: Single query with JOIN\nconst users = await db.users.find()\n  .populate('posts'); \u002F\u002F 1 query\n```\n\n**Problem: Missing Index**\n```sql\n-- Check slow query\nEXPLAIN SELECT * FROM users WHERE email = 'test@example.com';\n-- Shows: Seq Scan (bad)\n\n-- Add index\nCREATE INDEX idx_users_email ON users(email);\n\n-- Check again\nEXPLAIN SELECT * FROM users WHERE email = 'test@example.com';\n-- Shows: Index Scan (good)\n```\n\n**Problem: SELECT ***\n```javascript\n\u002F\u002F Bad: Fetches all columns\nconst users = await db.query('SELECT * FROM users');\n\n\u002F\u002F Good: Only needed columns\nconst users = await db.query('SELECT id, name, email FROM users');\n```\n\n**Problem: No Pagination**\n```javascript\n\u002F\u002F Bad: Returns all records\nconst users = await db.users.find();\n\n\u002F\u002F Good: Paginated\nconst users = await db.users.find()\n  .limit(20)\n  .skip((page - 1) * 20);\n```\n\n### API Performance\n\n**Problem: No Caching**\n```javascript\n\u002F\u002F Bad: Hits database every time\napp.get('\u002Fapi\u002Fstats', async (req, res) => {\n  const stats = await db.stats.calculate(); \u002F\u002F Slow\n  res.json(stats);\n});\n\n\u002F\u002F Good: Cache for 5 minutes\nconst cache = new Map();\napp.get('\u002Fapi\u002Fstats', async (req, res) => {\n  const cached = cache.get('stats');\n  if (cached && Date.now() - cached.time \u003C 300000) {\n    return res.json(cached.data);\n  }\n  \n  const stats = await db.stats.calculate();\n  cache.set('stats', { data: stats, time: Date.now() });\n  res.json(stats);\n});\n```\n\n**Problem: Sequential Operations**\n```javascript\n\u002F\u002F Bad: Sequential (slow)\nconst user = await getUser(id);\nconst posts = await getPosts(id);\nconst comments = await getComments(id);\n\u002F\u002F Total: 300ms + 200ms + 150ms = 650ms\n\n\u002F\u002F Good: Parallel (fast)\nconst [user, posts, comments] = await Promise.all([\n  getUser(id),\n  getPosts(id),\n  getComments(id)\n]);\n\u002F\u002F Total: max(300ms, 200ms, 150ms) = 300ms\n```\n\n**Problem: Large Payloads**\n```javascript\n\u002F\u002F Bad: Returns everything\nres.json(users); \u002F\u002F 5MB response\n\n\u002F\u002F Good: Only needed fields\nres.json(users.map(u => ({\n  id: u.id,\n  name: u.name,\n  email: u.email\n}))); \u002F\u002F 500KB response\n```\n\n### Frontend Performance\n\n**Problem: Unnecessary Re-renders**\n```javascript\n\u002F\u002F Bad: Re-renders on every parent update\nfunction UserList({ users }) {\n  return users.map(user => \u003CUserCard user={user} \u002F>);\n}\n\n\u002F\u002F Good: Memoized\nconst UserCard = React.memo(({ user }) => {\n  return \u003Cdiv>{user.name}\u003C\u002Fdiv>;\n});\n```\n\n**Problem: Large Bundle**\n```javascript\n\u002F\u002F Bad: Imports entire library\nimport _ from 'lodash'; \u002F\u002F 70KB\n\n\u002F\u002F Good: Import only what you need\nimport debounce from 'lodash\u002Fdebounce'; \u002F\u002F 2KB\n```\n\n**Problem: No Code Splitting**\n```javascript\n\u002F\u002F Bad: Everything in one bundle\nimport HeavyComponent from '.\u002FHeavyComponent';\n\n\u002F\u002F Good: Lazy load\nconst HeavyComponent = React.lazy(() => import('.\u002FHeavyComponent'));\n```\n\n**Problem: Unoptimized Images**\n```html\n\u003C!-- Bad: Large image -->\n\u003Cimg src=\"photo.jpg\" \u002F> \u003C!-- 5MB -->\n\n\u003C!-- Good: Optimized and responsive -->\n\u003Cimg \n  src=\"photo-small.webp\" \n  srcset=\"photo-small.webp 400w, photo-large.webp 800w\"\n  loading=\"lazy\"\n  width=\"400\"\n  height=\"300\"\n\u002F> \u003C!-- 50KB -->\n```\n\n### Algorithm Optimization\n\n**Problem: Inefficient Algorithm**\n```javascript\n\u002F\u002F Bad: O(n²) - nested loops\nfunction findDuplicates(arr) {\n  const duplicates = [];\n  for (let i = 0; i \u003C arr.length; i++) {\n    for (let j = i + 1; j \u003C arr.length; j++) {\n      if (arr[i] === arr[j]) duplicates.push(arr[i]);\n    }\n  }\n  return duplicates;\n}\n\n\u002F\u002F Good: O(n) - single pass with Set\nfunction findDuplicates(arr) {\n  const seen = new Set();\n  const duplicates = new Set();\n  for (const item of arr) {\n    if (seen.has(item)) duplicates.add(item);\n    seen.add(item);\n  }\n  return Array.from(duplicates);\n}\n```\n\n**Problem: Repeated Calculations**\n```javascript\n\u002F\u002F Bad: Calculates every time\nfunction getTotal(items) {\n  return items.reduce((sum, item) => sum + item.price * item.quantity, 0);\n}\n\u002F\u002F Called 100 times in render\n\n\u002F\u002F Good: Memoized\nconst getTotal = useMemo(() => {\n  return items.reduce((sum, item) => sum + item.price * item.quantity, 0);\n}, [items]);\n```\n\n### Memory Optimization\n\n**Problem: Memory Leak**\n```javascript\n\u002F\u002F Bad: Event listener not cleaned up\nuseEffect(() => {\n  window.addEventListener('scroll', handleScroll);\n  \u002F\u002F Memory leak!\n}, []);\n\n\u002F\u002F Good: Cleanup\nuseEffect(() => {\n  window.addEventListener('scroll', handleScroll);\n  return () => window.removeEventListener('scroll', handleScroll);\n}, []);\n```\n\n**Problem: Large Data in Memory**\n```javascript\n\u002F\u002F Bad: Loads entire file into memory\nconst data = fs.readFileSync('huge-file.txt'); \u002F\u002F 1GB\n\n\u002F\u002F Good: Stream it\nconst stream = fs.createReadStream('huge-file.txt');\nstream.on('data', chunk => process(chunk));\n```\n\n## Measuring Impact\n\nAlways measure before and after:\n\n```javascript\n\u002F\u002F Before optimization\nconsole.time('query');\nconst users = await db.users.find();\nconsole.timeEnd('query');\n\u002F\u002F query: 2341ms\n\n\u002F\u002F After optimization (added index)\nconsole.time('query');\nconst users = await db.users.find();\nconsole.timeEnd('query');\n\u002F\u002F query: 23ms\n\n\u002F\u002F Improvement: 100x faster!\n```\n\n## Performance Budgets\n\nSet targets:\n\n```\nPage Load: \u003C 2 seconds\nAPI Response: \u003C 200ms\nDatabase Query: \u003C 50ms\nBundle Size: \u003C 200KB\nTime to Interactive: \u003C 3 seconds\n```\n\n## Tools\n\n**Browser:**\n- Chrome DevTools Performance tab\n- Lighthouse (audit)\n- Network tab (waterfall)\n\n**Node.js:**\n- `node --prof` (profiling)\n- `clinic` (diagnostics)\n- `autocannon` (load testing)\n\n**Database:**\n- `EXPLAIN ANALYZE` (query plans)\n- Slow query log\n- Database profiler\n\n**Monitoring:**\n- New Relic\n- Datadog\n- Sentry Performance\n\n## Quick Wins\n\nEasy optimizations with big impact:\n\n1. **Add database indexes** on frequently queried columns\n2. **Enable gzip compression** on server\n3. **Add caching** for expensive operations\n4. **Lazy load** images and heavy components\n5. **Use CDN** for static assets\n6. **Minify and compress** JavaScript\u002FCSS\n7. **Remove unused dependencies**\n8. **Use pagination** instead of loading all data\n9. **Optimize images** (WebP, proper sizing)\n10. **Enable HTTP\u002F2** on server\n\n## Optimization Checklist\n\n- [ ] Measured current performance\n- [ ] Identified bottleneck\n- [ ] Applied optimization\n- [ ] Measured improvement\n- [ ] Verified functionality still works\n- [ ] No new bugs introduced\n- [ ] Documented the change\n\n## When NOT to Optimize\n\n- Premature optimization (optimize when it's actually slow)\n- Micro-optimizations (save 1ms when page takes 5 seconds)\n- Readable code is more important than tiny speed gains\n- If it's already fast enough\n\n## Key Principles\n\n- Measure before optimizing\n- Fix the biggest bottleneck first\n- Measure after to prove improvement\n- Don't sacrifice readability for tiny gains\n- Profile in production-like environment\n- Consider the 80\u002F20 rule (20% of code causes 80% of slowness)\n\n## Related Skills\n\n- `@database-design` - Query optimization\n- `@codebase-audit-pre-push` - Code review\n- `@bug-hunter` - Debugging\n","# Performance Optimizer\n\nFind and fix performance bottlenecks. Measure, optimize, verify. Make it fast.\n\n## When to Use This Skill\n\n- App is slow or laggy\n- User complains about performance\n- Page load times are high\n- API responses are slow\n- Database queries take too long\n- User mentions \"slow\", \"lag\", \"performance\", or \"optimize\"\n\n## The Optimization Process\n\n### 1. Measure First\n\nNever optimize without measuring:\n\n```javascript\n\u002F\u002F Measure execution time\nconsole.time('operation');\nawait slowOperation();\nconsole.timeEnd('operation'); \u002F\u002F operation: 2341ms\n```\n\n**What to measure:**\n- Page load time\n- API response time\n- Database query time\n- Function execution time\n- Memory usage\n- Network requests\n\n### 2. Find the Bottleneck\n\nUse profiling tools to find the slow parts:\n\n**Browser:**\n```\nDevTools → Performance tab → Record → Stop\nLook for long tasks (red bars)\n```\n\n**Node.js:**\n```bash\nnode --prof app.js\nnode --prof-process isolate-*.log > profile.txt\n```\n\n**Database:**\n```sql\nEXPLAIN ANALYZE SELECT * FROM users WHERE email = 'test@example.com';\n```\n\n### 3. Optimize\n\nFix the slowest thing first (biggest impact).\n\n## Common Optimizations\n\n### Database Queries\n\n**Problem: N+1 Queries**\n```javascript\n\u002F\u002F Bad: N+1 queries\nconst users = await db.users.find();\nfor (const user of users) {\n  user.posts = await db.posts.find({ userId: user.id }); \u002F\u002F N queries\n}\n\n\u002F\u002F Good: Single query with JOIN\nconst users = await db.users.find()\n  .populate('posts'); \u002F\u002F 1 query\n```\n\n**Problem: Missing Index**\n```sql\n-- Check slow query\nEXPLAIN SELECT * FROM users WHERE email = 'test@example.com';\n-- Shows: Seq Scan (bad)\n\n-- Add index\nCREATE INDEX idx_users_email ON users(email);\n\n-- Check again\nEXPLAIN SELECT * FROM users WHERE email = 'test@example.com';\n-- Shows: Index Scan (good)\n```\n\n**Problem: SELECT ***\n```javascript\n\u002F\u002F Bad: Fetches all columns\nconst users = await db.query('SELECT * FROM users');\n\n\u002F\u002F Good: Only needed columns\nconst users = await db.query('SELECT id, name, email FROM users');\n```\n\n**Problem: No Pagination**\n```javascript\n\u002F\u002F Bad: Returns all records\nconst users = await db.users.find();\n\n\u002F\u002F Good: Paginated\nconst users = await db.users.find()\n  .limit(20)\n  .skip((page - 1) * 20);\n```\n\n### API Performance\n\n**Problem: No Caching**\n```javascript\n\u002F\u002F Bad: Hits database every time\napp.get('\u002Fapi\u002Fstats', async (req, res) => {\n  const stats = await db.stats.calculate(); \u002F\u002F Slow\n  res.json(stats);\n});\n\n\u002F\u002F Good: Cache for 5 minutes\nconst cache = new Map();\napp.get('\u002Fapi\u002Fstats', async (req, res) => {\n  const cached = cache.get('stats');\n  if (cached && Date.now() - cached.time \u003C 300000) {\n    return res.json(cached.data);\n  }\n  \n  const stats = await db.stats.calculate();\n  cache.set('stats', { data: stats, time: Date.now() });\n  res.json(stats);\n});\n```\n\n**Problem: Sequential Operations**\n```javascript\n\u002F\u002F Bad: Sequential (slow)\nconst user = await getUser(id);\nconst posts = await getPosts(id);\nconst comments = await getComments(id);\n\u002F\u002F Total: 300ms + 200ms + 150ms = 650ms\n\n\u002F\u002F Good: Parallel (fast)\nconst [user, posts, comments] = await Promise.all([\n  getUser(id),\n  getPosts(id),\n  getComments(id)\n]);\n\u002F\u002F Total: max(300ms, 200ms, 150ms) = 300ms\n```\n\n**Problem: Large Payloads**\n```javascript\n\u002F\u002F Bad: Returns everything\nres.json(users); \u002F\u002F 5MB response\n\n\u002F\u002F Good: Only needed fields\nres.json(users.map(u => ({\n  id: u.id,\n  name: u.name,\n  email: u.email\n}))); \u002F\u002F 500KB response\n```\n\n### Frontend Performance\n\n**Problem: Unnecessary Re-renders**\n```javascript\n\u002F\u002F Bad: Re-renders on every parent update\nfunction UserList({ users }) {\n  return users.map(user => \u003CUserCard user={user} \u002F>);\n}\n\n\u002F\u002F Good: Memoized\nconst UserCard = React.memo(({ user }) => {\n  return \u003Cdiv>{user.name}\u003C\u002Fdiv>;\n});\n```\n\n**Problem: Large Bundle**\n```javascript\n\u002F\u002F Bad: Imports entire library\nimport _ from 'lodash'; \u002F\u002F 70KB\n\n\u002F\u002F Good: Import only what you need\nimport debounce from 'lodash\u002Fdebounce'; \u002F\u002F 2KB\n```\n\n**Problem: No Code Splitting**\n```javascript\n\u002F\u002F Bad: Everything in one bundle\nimport HeavyComponent from '.\u002FHeavyComponent';\n\n\u002F\u002F Good: Lazy load\nconst HeavyComponent = React.lazy(() => import('.\u002FHeavyComponent'));\n```\n\n**Problem: Unoptimized Images**\n```html\n\u003C!-- Bad: Large image -->\n\u003Cimg src=\"photo.jpg\" \u002F> \u003C!-- 5MB -->\n\n\u003C!-- Good: Optimized and responsive -->\n\u003Cimg \n  src=\"photo-small.webp\" \n  srcset=\"photo-small.webp 400w, photo-large.webp 800w\"\n  loading=\"lazy\"\n  width=\"400\"\n  height=\"300\"\n\u002F> \u003C!-- 50KB -->\n```\n\n### Algorithm Optimization\n\n**Problem: Inefficient Algorithm**\n```javascript\n\u002F\u002F Bad: O(n²) - nested loops\nfunction findDuplicates(arr) {\n  const duplicates = [];\n  for (let i = 0; i \u003C arr.length; i++) {\n    for (let j = i + 1; j \u003C arr.length; j++) {\n      if (arr[i] === arr[j]) duplicates.push(arr[i]);\n    }\n  }\n  return duplicates;\n}\n\n\u002F\u002F Good: O(n) - single pass with Set\nfunction findDuplicates(arr) {\n  const seen = new Set();\n  const duplicates = new Set();\n  for (const item of arr) {\n    if (seen.has(item)) duplicates.add(item);\n    seen.add(item);\n  }\n  return Array.from(duplicates);\n}\n```\n\n**Problem: Repeated Calculations**\n```javascript\n\u002F\u002F Bad: Calculates every time\nfunction getTotal(items) {\n  return items.reduce((sum, item) => sum + item.price * item.quantity, 0);\n}\n\u002F\u002F Called 100 times in render\n\n\u002F\u002F Good: Memoized\nconst getTotal = useMemo(() => {\n  return items.reduce((sum, item) => sum + item.price * item.quantity, 0);\n}, [items]);\n```\n\n### Memory Optimization\n\n**Problem: Memory Leak**\n```javascript\n\u002F\u002F Bad: Event listener not cleaned up\nuseEffect(() => {\n  window.addEventListener('scroll', handleScroll);\n  \u002F\u002F Memory leak!\n}, []);\n\n\u002F\u002F Good: Cleanup\nuseEffect(() => {\n  window.addEventListener('scroll', handleScroll);\n  return () => window.removeEventListener('scroll', handleScroll);\n}, []);\n```\n\n**Problem: Large Data in Memory**\n```javascript\n\u002F\u002F Bad: Loads entire file into memory\nconst data = fs.readFileSync('huge-file.txt'); \u002F\u002F 1GB\n\n\u002F\u002F Good: Stream it\nconst stream = fs.createReadStream('huge-file.txt');\nstream.on('data', chunk => process(chunk));\n```\n\n## Measuring Impact\n\nAlways measure before and after:\n\n```javascript\n\u002F\u002F Before optimization\nconsole.time('query');\nconst users = await db.users.find();\nconsole.timeEnd('query');\n\u002F\u002F query: 2341ms\n\n\u002F\u002F After optimization (added index)\nconsole.time('query');\nconst users = await db.users.find();\nconsole.timeEnd('query');\n\u002F\u002F query: 23ms\n\n\u002F\u002F Improvement: 100x faster!\n```\n\n## Performance Budgets\n\nSet targets:\n\n```\nPage Load: \u003C 2 seconds\nAPI Response: \u003C 200ms\nDatabase Query: \u003C 50ms\nBundle Size: \u003C 200KB\nTime to Interactive: \u003C 3 seconds\n```\n\n## Tools\n\n**Browser:**\n- Chrome DevTools Performance tab\n- Lighthouse (audit)\n- Network tab (waterfall)\n\n**Node.js:**\n- `node --prof` (profiling)\n- `clinic` (diagnostics)\n- `autocannon` (load testing)\n\n**Database:**\n- `EXPLAIN ANALYZE` (query plans)\n- Slow query log\n- Database profiler\n\n**Monitoring:**\n- New Relic\n- Datadog\n- Sentry Performance\n\n## Quick Wins\n\nEasy optimizations with big impact:\n\n1. **Add database indexes** on frequently queried columns\n2. **Enable gzip compression** on server\n3. **Add caching** for expensive operations\n4. **Lazy load** images and heavy components\n5. **Use CDN** for static assets\n6. **Minify and compress** JavaScript\u002FCSS\n7. **Remove unused dependencies**\n8. **Use pagination** instead of loading all data\n9. **Optimize images** (WebP, proper sizing)\n10. **Enable HTTP\u002F2** on server\n\n## Optimization Checklist\n\n- [ ] Measured current performance\n- [ ] Identified bottleneck\n- [ ] Applied optimization\n- [ ] Measured improvement\n- [ ] Verified functionality still works\n- [ ] No new bugs introduced\n- [ ] Documented the change\n\n## When NOT to Optimize\n\n- Premature optimization (optimize when it's actually slow)\n- Micro-optimizations (save 1ms when page takes 5 seconds)\n- Readable code is more important than tiny speed gains\n- If it's already fast enough\n\n## Key Principles\n\n- Measure before optimizing\n- Fix the biggest bottleneck first\n- Measure after to prove improvement\n- Don't sacrifice readability for tiny gains\n- Profile in production-like environment\n- Consider the 80\u002F20 rule (20% of code causes 80% of slowness)\n\n## Related Skills\n\n- `@database-design` - Query optimization\n- `@codebase-audit-pre-push` - Code review\n- `@bug-hunter` - Debugging\n",{"name":5,"metadata":36,"description":7},{"risk":22,"source":27,"category":23,"date_added":37},"2026-03-05","main","2b749c82b5d11fac39d9a6e021ce3f5b8a541bd1","cli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fperformance-optimizer",3909,"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","2026-11-11 11:53:30",{"source":8,"skillName":5,"commands":49,"prompt":59,"zipAvailable":60},[50,53,56],{"tool":51,"command":52},"npx","npx skills add davila7\u002Fclaude-code-templates --skill performance-optimizer",{"tool":54,"command":55},"bunx","bunx skills add davila7\u002Fclaude-code-templates --skill performance-optimizer",{"tool":57,"command":58},"pnpm","pnpm dlx skills add davila7\u002Fclaude-code-templates --skill performance-optimizer","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fperformance-optimizer\u002FSKILL.md",true,[62],{"path":63,"resourceType":64,"resourceTypeDesc":65,"sizeBytes":66,"sourceHtmlUrl":67},"README.md","REFERENCE","参考文档",465,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fperformance-optimizer\u002FREADME.md",[69,101,127,160,195,219],{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":80,"publishedAt":31},"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",[75],{"categoryNo":76,"categoryName":77,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100],"scoring","pool","wealthville pool scoring","liquidity","which","for","exit","now","use","when","reduce","with","record","track","verdict","evm","solana","how","public","look",{"skillNo":102,"name":103,"nameZh":6,"description":104,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":105,"categories":106,"keywords":108,"publishedAt":31},"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",[107],{"categoryNo":76,"categoryName":77,"taxonomyType":78,"taxonomyTypeDesc":79},[109,110,111,112,113,114,115,116,117,118,119,90,24,120,121,122,123,124,125,126],"technical debt","debt","technical","technical debt auditor","auditor","coverage","complexity","markers","project","cleanup","unused","todo","work","plan","focus","signals","audit","dependency",{"skillNo":128,"name":129,"nameZh":6,"description":130,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":131,"categories":132,"keywords":142,"publishedAt":31},"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",[133,136,137],{"categoryNo":134,"categoryName":135,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":76,"categoryName":77,"taxonomyType":78,"taxonomyTypeDesc":79},{"categoryNo":138,"categoryName":139,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[143,144,145,146,147,148,149,86,150,151,152,153,154,155,156,89,157,158,90,159],"readonly","guard","sql guard","sql","readonly sql guard","erp","effect","read-only","db","just","tool","calls","only","MCP","access","database","query",{"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":164,"licenseFileUrl":165,"sourceHtmlUrl":166,"categories":167,"keywords":171,"publishedAt":31},"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",[168],{"categoryNo":169,"categoryName":170,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000009","前端开发",[172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,86,194],"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":196,"name":197,"nameZh":6,"description":198,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":164,"licenseFileUrl":199,"sourceHtmlUrl":200,"categories":201,"keywords":206,"publishedAt":31},"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",[202,205],{"categoryNo":203,"categoryName":204,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":169,"categoryName":170,"taxonomyType":78,"taxonomyTypeDesc":79},[207,208,209,210,211,173,212,182,183,213,214,215,216,86,217,92,218],"webapp testing","testing","webapp","browser","playwright","applications","debugging","toolkit","logs","screenshots","local","behavior",{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":164,"licenseFileUrl":223,"sourceHtmlUrl":224,"categories":225,"keywords":233,"publishedAt":31},"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",[226,229,230],{"categoryNo":227,"categoryName":228,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":76,"categoryName":77,"taxonomyType":78,"taxonomyTypeDesc":79},{"categoryNo":231,"categoryName":232,"taxonomyType":140,"taxonomyTypeDesc":141},"01JBSEEDCAT000000000000036","内容创作者",[234,235,236,237,238,239,240,241,175,242,185,24,243,244,245,246,247,155,248,90,249,250,251,252,253,98,254],"discernment nudge","nudge","interpretation","help","run","reasoning","data","writing","lookup","content","review","conversation","short","up","invoke","you","analysis","claims","argument","assemble","recommendations"]