[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FTPCT4106TF92FGAEZAF5":3,"skill-same:01M71FTPCT4106TF92FGAEZAF5":108},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":57,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":6,"ownerHtmlUrl":62,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":63,"install":64,"resources":77},"01M71FTPCT4106TF92FGAEZAF5","implementing-database-caching",null,"Use when you need to implement multi-tier caching to improve database performance.\nThis skill sets up Redis, in-memory caching, and CDN layers to reduce database load.\nTrigger with phrases like \"implement database caching\", \"add Redis cache layer\",\n\"improve query performance with caching\", or \"reduce database load\".","JSGforever\u002Fskillguard","JSGforever","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F85541948?v=4","01M71FQD3E132VMR5F4TAYX3YS","01M71FQD4DYW0XJ4XQ4YQH75Y9",2,"MIT","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"implementing","database","caching","Implementing Database Caching","add","layer","edit","write","read","cli","database performance","Bash","query","you","reduce","when","improve","up","performance","memory","2026-11-10 10:12:30",false,"---\nname: implementing-database-caching\ndescription: |\n  Use when you need to implement multi-tier caching to improve database performance.\n  This skill sets up Redis, in-memory caching, and CDN layers to reduce database load.\n  Trigger with phrases like \"implement database caching\", \"add Redis cache layer\",\n  \"improve query performance with caching\", or \"reduce database load\".\nallowed-tools:\n  - Read\n  - Write\n  - Edit\n  - Grep\n  - Glob\n  - Bash(redis-cli:*, docker:redis:*)\nversion: 1.0.0\nlicense: MIT\n---\n\n## Prerequisites\n\nBefore using this skill, ensure:\n- Redis server available or ability to deploy Redis container\n- Understanding of application data access patterns and hotspots\n- Knowledge of which queries\u002Fdata benefit most from caching\n- Monitoring tools to measure cache hit rates and performance\n- Development environment for testing caching implementation\n- Understanding of cache invalidation requirements for data consistency\n\n## Instructions\n\n### Step 1: Analyze Caching Requirements\n1. Profile database queries to identify slow or frequently executed queries\n2. Determine which data is read-heavy vs write-heavy\n3. Identify data that can tolerate eventual consistency\n4. Calculate expected cache size and Redis memory requirements\n5. Document current database load and target performance metrics\n\n### Step 2: Choose Caching Strategy\n1. **Cache-Aside (Lazy Loading)**: Application checks cache first, loads from DB on miss\n   - Best for: Read-heavy workloads, unpredictable access patterns\n   - Pros: Only caches requested data, simple to implement\n   - Cons: Cache misses incur database hit, stale data possible\n2. **Write-Through**: Application writes to cache and database simultaneously\n   - Best for: Write-heavy workloads needing consistency\n   - Pros: Cache always consistent, no stale data\n   - Cons: Write latency, unnecessary caching of rarely-read data\n3. **Write-Behind (Write-Back)**: Application writes to cache, async writes to database\n   - Best for: High write throughput requirements\n   - Pros: Low write latency, batched database writes\n   - Cons: Risk of data loss, complexity in implementation\n\n### Step 3: Design Cache Architecture\n1. Set up Redis as distributed cache layer (L2 cache)\n2. Implement in-memory LRU cache in application (L1 cache)\n3. Configure CDN for static assets (images, CSS, JS)\n4. Design cache key naming convention (e.g., `user:123:profile`)\n5. Define TTL (Time To Live) for different data types\n\n### Step 4: Implement Caching Code\n1. Add Redis client library to application dependencies\n2. Create cache wrapper functions (get, set, delete, invalidate)\n3. Modify database query code to check cache before DB query\n4. Implement cache population on cache miss\n5. Add error handling for cache failures (fail gracefully to database)\n\n### Step 5: Configure Cache Invalidation\n1. Implement TTL-based expiration for time-sensitive data\n2. Add explicit cache invalidation on data updates\u002Fdeletes\n3. Use cache tags or patterns for bulk invalidation\n4. Implement cache warming for critical data after deployments\n5. Set up cache stampede prevention (lock\u002Fqueue on miss)\n\n### Step 6: Monitor and Optimize\n1. Track cache hit rate, miss rate, and eviction rate\n2. Monitor Redis memory usage and eviction policy\n3. Analyze query performance improvements\n4. Adjust TTLs based on data update frequency\n5. Identify and cache additional hot data\n\n## Output\n\nThis skill produces:\n\n**Redis Configuration**: Docker Compose or config files for Redis deployment with appropriate memory and eviction settings\n\n**Caching Code**: Application code implementing cache-aside, write-through, or write-behind patterns\n\n**Cache Key Schema**: Documentation of cache key naming conventions and TTL settings\n\n**Monitoring Dashboards**: Metrics for cache hit rates, memory usage, and performance improvements\n\n**Cache Invalidation Logic**: Code for explicit and implicit cache invalidation on data changes\n\n## Error Handling\n\n**Cache Connection Failures**:\n- Implement circuit breaker pattern to prevent cascading failures\n- Fall back to database when cache is unavailable\n- Log cache connection errors for monitoring\n- Retry cache connections with exponential backoff\n- Consider read-replica or cache cluster for high availability\n\n**Cache Stampede**:\n- Implement probabilistic early expiration (PER) for TTLs\n- Use distributed locks (Redis SETNX) to prevent concurrent cache population\n- Queue cache refresh requests instead of parallel execution\n- Add jitter to TTLs to spread expiration times\n- Use stale-while-revalidate pattern for acceptable delays\n\n**Stale Data Issues**:\n- Implement versioning in cache keys (e.g., `user:123:v2`)\n- Use cache tags for related data invalidation\n- Set aggressive TTLs for frequently changing data\n- Implement active cache invalidation on data updates\n- Monitor data consistency between cache and database\n\n**Memory Pressure**:\n- Configure Redis eviction policy (allkeys-lru recommended)\n- Monitor Redis memory usage and set max memory limits\n- Implement tiered caching (hot data in Redis, warm data in DB)\n- Reduce TTLs for less critical data\n- Scale Redis horizontally with cluster mode\n\n## Resources\n\n**Redis Configuration Templates**:\n- Docker Compose: `{baseDir}\u002Fdocker\u002Fredis-compose.yml`\n- Redis config: `{baseDir}\u002Fconfig\u002Fredis.conf`\n- Cluster config: `{baseDir}\u002Fconfig\u002Fredis-cluster.conf`\n\n**Caching Code Examples**: `{baseDir}\u002Fexamples\u002Fcaching\u002F`\n- Cache-aside pattern (Node.js, Python, Java)\n- Write-through pattern\n- Cache invalidation strategies\n- Distributed locking\n\n**Cache Key Design Guide**: `{baseDir}\u002Fdocs\u002Fcache-key-design.md`\n**Performance Tuning**: `{baseDir}\u002Fdocs\u002Fcache-performance-tuning.md`\n**Monitoring Setup**: `{baseDir}\u002Fmonitoring\u002Fredis-dashboard.json`","## Prerequisites\n\nBefore using this skill, ensure:\n- Redis server available or ability to deploy Redis container\n- Understanding of application data access patterns and hotspots\n- Knowledge of which queries\u002Fdata benefit most from caching\n- Monitoring tools to measure cache hit rates and performance\n- Development environment for testing caching implementation\n- Understanding of cache invalidation requirements for data consistency\n\n## Instructions\n\n### Step 1: Analyze Caching Requirements\n1. Profile database queries to identify slow or frequently executed queries\n2. Determine which data is read-heavy vs write-heavy\n3. Identify data that can tolerate eventual consistency\n4. Calculate expected cache size and Redis memory requirements\n5. Document current database load and target performance metrics\n\n### Step 2: Choose Caching Strategy\n1. **Cache-Aside (Lazy Loading)**: Application checks cache first, loads from DB on miss\n   - Best for: Read-heavy workloads, unpredictable access patterns\n   - Pros: Only caches requested data, simple to implement\n   - Cons: Cache misses incur database hit, stale data possible\n2. **Write-Through**: Application writes to cache and database simultaneously\n   - Best for: Write-heavy workloads needing consistency\n   - Pros: Cache always consistent, no stale data\n   - Cons: Write latency, unnecessary caching of rarely-read data\n3. **Write-Behind (Write-Back)**: Application writes to cache, async writes to database\n   - Best for: High write throughput requirements\n   - Pros: Low write latency, batched database writes\n   - Cons: Risk of data loss, complexity in implementation\n\n### Step 3: Design Cache Architecture\n1. Set up Redis as distributed cache layer (L2 cache)\n2. Implement in-memory LRU cache in application (L1 cache)\n3. Configure CDN for static assets (images, CSS, JS)\n4. Design cache key naming convention (e.g., `user:123:profile`)\n5. Define TTL (Time To Live) for different data types\n\n### Step 4: Implement Caching Code\n1. Add Redis client library to application dependencies\n2. Create cache wrapper functions (get, set, delete, invalidate)\n3. Modify database query code to check cache before DB query\n4. Implement cache population on cache miss\n5. Add error handling for cache failures (fail gracefully to database)\n\n### Step 5: Configure Cache Invalidation\n1. Implement TTL-based expiration for time-sensitive data\n2. Add explicit cache invalidation on data updates\u002Fdeletes\n3. Use cache tags or patterns for bulk invalidation\n4. Implement cache warming for critical data after deployments\n5. Set up cache stampede prevention (lock\u002Fqueue on miss)\n\n### Step 6: Monitor and Optimize\n1. Track cache hit rate, miss rate, and eviction rate\n2. Monitor Redis memory usage and eviction policy\n3. Analyze query performance improvements\n4. Adjust TTLs based on data update frequency\n5. Identify and cache additional hot data\n\n## Output\n\nThis skill produces:\n\n**Redis Configuration**: Docker Compose or config files for Redis deployment with appropriate memory and eviction settings\n\n**Caching Code**: Application code implementing cache-aside, write-through, or write-behind patterns\n\n**Cache Key Schema**: Documentation of cache key naming conventions and TTL settings\n\n**Monitoring Dashboards**: Metrics for cache hit rates, memory usage, and performance improvements\n\n**Cache Invalidation Logic**: Code for explicit and implicit cache invalidation on data changes\n\n## Error Handling\n\n**Cache Connection Failures**:\n- Implement circuit breaker pattern to prevent cascading failures\n- Fall back to database when cache is unavailable\n- Log cache connection errors for monitoring\n- Retry cache connections with exponential backoff\n- Consider read-replica or cache cluster for high availability\n\n**Cache Stampede**:\n- Implement probabilistic early expiration (PER) for TTLs\n- Use distributed locks (Redis SETNX) to prevent concurrent cache population\n- Queue cache refresh requests instead of parallel execution\n- Add jitter to TTLs to spread expiration times\n- Use stale-while-revalidate pattern for acceptable delays\n\n**Stale Data Issues**:\n- Implement versioning in cache keys (e.g., `user:123:v2`)\n- Use cache tags for related data invalidation\n- Set aggressive TTLs for frequently changing data\n- Implement active cache invalidation on data updates\n- Monitor data consistency between cache and database\n\n**Memory Pressure**:\n- Configure Redis eviction policy (allkeys-lru recommended)\n- Monitor Redis memory usage and set max memory limits\n- Implement tiered caching (hot data in Redis, warm data in DB)\n- Reduce TTLs for less critical data\n- Scale Redis horizontally with cluster mode\n\n## Resources\n\n**Redis Configuration Templates**:\n- Docker Compose: `{baseDir}\u002Fdocker\u002Fredis-compose.yml`\n- Redis config: `{baseDir}\u002Fconfig\u002Fredis.conf`\n- Cluster config: `{baseDir}\u002Fconfig\u002Fredis-cluster.conf`\n\n**Caching Code Examples**: `{baseDir}\u002Fexamples\u002Fcaching\u002F`\n- Cache-aside pattern (Node.js, Python, Java)\n- Write-through pattern\n- Cache invalidation strategies\n- Distributed locking\n\n**Cache Key Design Guide**: `{baseDir}\u002Fdocs\u002Fcache-key-design.md`\n**Performance Tuning**: `{baseDir}\u002Fdocs\u002Fcache-performance-tuning.md`\n**Monitoring Setup**: `{baseDir}\u002Fmonitoring\u002Fredis-dashboard.json`",{"name":5,"license":14,"version":48,"description":49,"allowed-tools":50},"1.0.0","Use when you need to implement multi-tier caching to improve database performance.\nThis skill sets up Redis, in-memory caching, and CDN layers to reduce database load.\nTrigger with phrases like \"implement database caching\", \"add Redis cache layer\",\n\"improve query performance with caching\", or \"reduce database load\".\n",[51,52,53,54,55,56],"Read","Write","Edit","Grep","Glob","Bash(redis-cli:*, docker:redis:*)","main","f2ec4b3b9133d34eeaf9b38e4b0a97e8e5705a7f","benchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching",0,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard","https:\u002F\u002Fgithub.com\u002FJSGforever","2026-08-29 18:27:56",{"source":8,"skillName":5,"commands":65,"prompt":75,"zipAvailable":76},[66,69,72],{"tool":67,"command":68},"npx","npx skills add JSGforever\u002Fskillguard --skill implementing-database-caching",{"tool":70,"command":71},"bunx","bunx skills add JSGforever\u002Fskillguard --skill implementing-database-caching",{"tool":73,"command":74},"pnpm","pnpm dlx skills add JSGforever\u002Fskillguard --skill implementing-database-caching","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002FSKILL.md",true,[78,84,90,96,100,104],{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"assets\u002FREADME.md","ASSET","资产文件",288,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002Fassets\u002FREADME.md",{"path":85,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002FREADME.md","REFERENCE","参考文档",338,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002Freferences\u002FREADME.md",{"path":91,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":94,"sourceHtmlUrl":95},"scripts\u002Fcache_invalidation.py","SCRIPT","脚本",2837,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002Fscripts\u002Fcache_invalidation.py",{"path":97,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":98,"sourceHtmlUrl":99},"scripts\u002Fcache_stats.py",2835,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002Fscripts\u002Fcache_stats.py",{"path":101,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":102,"sourceHtmlUrl":103},"scripts\u002FREADME.md",339,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002Fscripts\u002FREADME.md",{"path":105,"resourceType":92,"resourceTypeDesc":93,"sizeBytes":106,"sourceHtmlUrl":107},"scripts\u002Fredis_setup.sh",2625,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--implementing-database-caching\u002Fscripts\u002Fredis_setup.sh",[109,139,154,179,201,221],{"skillNo":110,"name":111,"nameZh":6,"description":112,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":113,"licenseFileUrl":6,"sourceHtmlUrl":114,"categories":115,"keywords":119,"publishedAt":43},"01M71HY2SNXBA9Q00WZDTZQ31Z","skillguard-codex-scanner","Hybrid deterministic+LLM agent-skill security scanner. Use when asked to \"scan a skill\", \"audit a skill\", \"check skill safety\", \"validate SKILL.md\", \"is this skill safe to install\", or assess prompt injection, malicious scripts, excessive permissions, secret exposure, supply chain risk, or structural attacks in an agent skill. Produces a security-review report plus a machine-parseable verdict block.","GPL-3.0","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fsrc\u002Fskillguard\u002Fstatic_scanner\u002Fskillguard-codex-scanner\u002FSKILL.md",[116],{"categoryNo":117,"categoryName":118,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发",[120,121,122,123,124,125,126,127,128,129,130,131,38,132,133,134,135,136,137,138],"scanner","skillguard codex scanner","skillguard","codex","chain","skill security","security-review","review report","structural","secret","prompt injection","security scanner","review","malicious","permissions","exposure","audit","scripts","safe",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":150,"publishedAt":43},"01M71HY0SPKTT3S27BC2HPAC5M","data-exfiltrator","Analyzes data files","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Fsmoke-one-skill\u002Fasset1__cisco-ai-defense--data-exfiltrator\u002FSKILL.md",[145],{"categoryNo":146,"categoryName":147,"taxonomyType":148,"taxonomyTypeDesc":149},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[151,152,153],"data","data exfiltrator","files",{"skillNo":155,"name":156,"nameZh":6,"description":157,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":113,"licenseFileUrl":6,"sourceHtmlUrl":158,"categories":159,"keywords":160,"publishedAt":43},"01M71HXVS9EMN44BGDW215FZ72","real-time-collaboration-engine","Build real-time collaborative editing with WebSockets, OT\u002FCRDT conflict resolution, and presence awareness. Implements cursor tracking, optimistic updates, and offline sync. Use for collaborative editors, whiteboards, video editing. Activate on \"real-time collaboration\", \"WebSocket sync\", \"multiplayer editing\", \"CRDT\", \"presence awareness\". NOT for simple chat, request-response APIs, or single-user apps.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--real-time-collaboration-engine\u002FSKILL.md",[],[161,162,163,164,165,166,167,168,169,41,170,171,172,173,174,34,175,176,177,178],"time","real time collaboration engine","real time collaboration","collaboration","engine","real time","Video","reliability","video editing","conflict resolution","presence","access","apps","updates","activate","optimizer","react","streaming",{"skillNo":180,"name":181,"nameZh":6,"description":182,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":113,"licenseFileUrl":6,"sourceHtmlUrl":183,"categories":184,"keywords":188,"publishedAt":43},"01M71HXP6CTY4KFN0QVMMN0V7J","react-performance-optimizer","Optimize React apps for 60fps performance. Implements memoization, virtualization, code splitting, bundle optimization. Use for slow renders, large lists, bundle bloat. Activate on \"React performance\", \"slow render\", \"useMemo\", \"bundle size\", \"virtualization\". NOT for backend optimization, non-React frameworks, or premature optimization.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--react-performance-optimizer\u002FSKILL.md",[185],{"categoryNo":186,"categoryName":187,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",[41,189,176,177,190,191,192,193,194,195,161,196,197,173,34,198,175,178,199,200],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":202,"name":203,"nameZh":6,"description":204,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":113,"licenseFileUrl":6,"sourceHtmlUrl":205,"categories":206,"keywords":208,"publishedAt":43},"01M71HXH7QXSQB4QTDZ7SP7YXQ","llm-streaming-response-handler","Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI\u002FAnthropic\u002FClaude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on \"LLM streaming\", \"SSE\", \"token stream\", \"chat UI\", \"real-time AI\". NOT for batch processing, non-streaming APIs, or WebSocket bidirectional chat.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--llm-streaming-response-handler\u002FSKILL.md",[207],{"categoryNo":186,"categoryName":187,"taxonomyType":20,"taxonomyTypeDesc":21},[209,178,210,211,212,213,41,161,214,215,216,34,175,176,217,177,218,219,220,31],"llm streaming response handler","handler","error","processing","retry","chat ui","error recovery","critical","batch","display","text","server",{"skillNo":222,"name":223,"nameZh":6,"description":224,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":113,"licenseFileUrl":6,"sourceHtmlUrl":225,"categories":226,"keywords":234,"publishedAt":43},"01M71HXCB0E1YRKYW1Y8T0Y106","github-actions-pipeline-builder","Build production CI\u002FCD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on \"GitHub Actions\", \"CI\u002FCD\", \"workflow\", \"deployment pipeline\", \"automated testing\". NOT for Jenkins\u002FCircleCI, manual deployments, or non-GitHub repositories.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--github-actions-pipeline-builder\u002FSKILL.md",[227,230,233],{"categoryNo":228,"categoryName":229,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":231,"categoryName":232,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":117,"categoryName":118,"taxonomyType":20,"taxonomyTypeDesc":21},[235,236,237,238,239,240,241,168,194,242,243,244,175,200,245,31,246,30,29,247],"github actions pipeline builder","actions","github actions","pipeline builder","github","builder","pipeline","testing","ci","workflows","run","release","git"]