[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71FSH8MP2XMS0CDXVS23QT8":3,"skill-same:01M71FSH8MP2XMS0CDXVS23QT8":102},{"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":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":51,"commitSha":52,"skillDirectory":53,"forksCount":54,"repositoryHtmlUrl":55,"repositoryHomepageUrl":6,"ownerHtmlUrl":56,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":57,"install":58,"resources":71},"01M71FSH8MP2XMS0CDXVS23QT8","analyzing-logs",null,"Analyze application logs for performance insights and issue detection including slow requests, error patterns, and resource usage. Use when troubleshooting performance issues or debugging errors. Trigger with phrases like \"analyze logs\", \"find slow requests\", or \"detect error patterns\".","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--analyzing-logs\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"logs","analyzing","Analyzing Logs","with","analyze","Bash","when","debugging","use","insights","errors","issues","trigger","performance","for","awk","performance insights","usage","error patterns","error","2026-11-10 10:12:30",false,"---\nname: analyzing-logs\ndescription: Analyze application logs for performance insights and issue detection including slow requests, error patterns, and resource usage. Use when troubleshooting performance issues or debugging errors. Trigger with phrases like \"analyze logs\", \"find slow requests\", or \"detect error patterns\".\nversion: 1.0.0\nallowed-tools:\n- Read\n- Write\n- Bash(logs:*)\n- Bash(grep:*)\n- Bash(awk:*)\n- Grep\nlicense: MIT\n---\n## Overview\n\nThis skill empowers Claude to automatically analyze application logs, pinpoint performance bottlenecks, and identify recurring errors. It streamlines the debugging process and helps optimize application performance by extracting key insights from log data.\n\n## How It Works\n\n1. **Initiate Analysis**: Claude activates the log analysis tool upon detecting relevant trigger phrases.\n2. **Log Data Extraction**: The tool extracts relevant data, including timestamps, request durations, error messages, and resource usage metrics.\n3. **Pattern Identification**: The tool identifies patterns such as slow requests, frequent errors, and resource exhaustion warnings.\n4. **Report Generation**: Claude presents a summary of findings, highlighting potential performance issues and optimization opportunities.\n\n## When to Use This Skill\n\nThis skill activates when you need to:\n- Identify performance bottlenecks in an application.\n- Debug recurring errors and exceptions.\n- Analyze log data for trends and anomalies.\n- Set up structured logging or log aggregation.\n\n## Examples\n\n### Example 1: Identifying Slow Requests\n\nUser request: \"Analyze logs for slow requests.\"\n\nThe skill will:\n1. Activate the log analysis tool.\n2. Identify requests exceeding predefined latency thresholds.\n3. Present a list of slow requests with corresponding timestamps and durations.\n\n### Example 2: Detecting Error Patterns\n\nUser request: \"Find error patterns in the application logs.\"\n\nThe skill will:\n1. Activate the log analysis tool.\n2. Scan logs for recurring error messages and exceptions.\n3. Group similar errors and present a summary of error frequencies.\n\n## Best Practices\n\n- **Log Level**: Ensure appropriate log levels (e.g., INFO, WARN, ERROR) are used to capture relevant information.\n- **Structured Logging**: Implement structured logging (e.g., JSON format) to facilitate efficient analysis.\n- **Log Rotation**: Configure log rotation policies to prevent log files from growing excessively.\n\n## Integration\n\nThis skill can be integrated with other tools for monitoring and alerting. For example, it can be used in conjunction with a monitoring plugin to automatically trigger alerts based on log analysis results. It can also work with deployment tools to rollback deployments when critical errors are detected in the logs.\n\n## Prerequisites\n\n- Access to application log files in {baseDir}\u002Flogs\u002F\n- Log parsing tools (grep, awk, sed)\n- Understanding of application log format and structure\n- Read permissions for log directories\n\n## Instructions\n\n1. Identify log files to analyze based on timeframe and application\n2. Extract relevant data (timestamps, durations, error messages)\n3. Apply pattern matching to identify slow requests and errors\n4. Aggregate and group similar issues\n5. Generate analysis report with findings and recommendations\n6. Suggest optimization opportunities based on patterns\n\n## Output\n\n- Summary of slow requests with response times\n- Error frequency reports grouped by type\n- Resource usage patterns and anomalies\n- Performance bottleneck identification\n- Recommendations for log improvements and optimizations\n\n## Error Handling\n\nIf log analysis fails:\n- Verify log file paths and permissions\n- Check log format compatibility\n- Validate timestamp parsing\n- Ensure sufficient disk space for analysis\n- Review log rotation configuration\n\n## Resources\n\n- Application logging best practices\n- Structured logging format guides\n- Log aggregation tools documentation\n- Performance analysis methodologies","## Overview\n\nThis skill empowers Claude to automatically analyze application logs, pinpoint performance bottlenecks, and identify recurring errors. It streamlines the debugging process and helps optimize application performance by extracting key insights from log data.\n\n## How It Works\n\n1. **Initiate Analysis**: Claude activates the log analysis tool upon detecting relevant trigger phrases.\n2. **Log Data Extraction**: The tool extracts relevant data, including timestamps, request durations, error messages, and resource usage metrics.\n3. **Pattern Identification**: The tool identifies patterns such as slow requests, frequent errors, and resource exhaustion warnings.\n4. **Report Generation**: Claude presents a summary of findings, highlighting potential performance issues and optimization opportunities.\n\n## When to Use This Skill\n\nThis skill activates when you need to:\n- Identify performance bottlenecks in an application.\n- Debug recurring errors and exceptions.\n- Analyze log data for trends and anomalies.\n- Set up structured logging or log aggregation.\n\n## Examples\n\n### Example 1: Identifying Slow Requests\n\nUser request: \"Analyze logs for slow requests.\"\n\nThe skill will:\n1. Activate the log analysis tool.\n2. Identify requests exceeding predefined latency thresholds.\n3. Present a list of slow requests with corresponding timestamps and durations.\n\n### Example 2: Detecting Error Patterns\n\nUser request: \"Find error patterns in the application logs.\"\n\nThe skill will:\n1. Activate the log analysis tool.\n2. Scan logs for recurring error messages and exceptions.\n3. Group similar errors and present a summary of error frequencies.\n\n## Best Practices\n\n- **Log Level**: Ensure appropriate log levels (e.g., INFO, WARN, ERROR) are used to capture relevant information.\n- **Structured Logging**: Implement structured logging (e.g., JSON format) to facilitate efficient analysis.\n- **Log Rotation**: Configure log rotation policies to prevent log files from growing excessively.\n\n## Integration\n\nThis skill can be integrated with other tools for monitoring and alerting. For example, it can be used in conjunction with a monitoring plugin to automatically trigger alerts based on log analysis results. It can also work with deployment tools to rollback deployments when critical errors are detected in the logs.\n\n## Prerequisites\n\n- Access to application log files in {baseDir}\u002Flogs\u002F\n- Log parsing tools (grep, awk, sed)\n- Understanding of application log format and structure\n- Read permissions for log directories\n\n## Instructions\n\n1. Identify log files to analyze based on timeframe and application\n2. Extract relevant data (timestamps, durations, error messages)\n3. Apply pattern matching to identify slow requests and errors\n4. Aggregate and group similar issues\n5. Generate analysis report with findings and recommendations\n6. Suggest optimization opportunities based on patterns\n\n## Output\n\n- Summary of slow requests with response times\n- Error frequency reports grouped by type\n- Resource usage patterns and anomalies\n- Performance bottleneck identification\n- Recommendations for log improvements and optimizations\n\n## Error Handling\n\nIf log analysis fails:\n- Verify log file paths and permissions\n- Check log format compatibility\n- Validate timestamp parsing\n- Ensure sufficient disk space for analysis\n- Review log rotation configuration\n\n## Resources\n\n- Application logging best practices\n- Structured logging format guides\n- Log aggregation tools documentation\n- Performance analysis methodologies",{"name":5,"license":14,"version":43,"description":7,"allowed-tools":44},"1.0.0",[45,46,47,48,49,50],"Read","Write","Bash(logs:*)","Bash(grep:*)","Bash(awk:*)","Grep","main","f2ec4b3b9133d34eeaf9b38e4b0a97e8e5705a7f","benchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs",0,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard","https:\u002F\u002Fgithub.com\u002FJSGforever","2026-08-29 18:27:56",{"source":8,"skillName":5,"commands":59,"prompt":69,"zipAvailable":70},[60,63,66],{"tool":61,"command":62},"npx","npx skills add JSGforever\u002Fskillguard --skill analyzing-logs",{"tool":64,"command":65},"bunx","bunx skills add JSGforever\u002Fskillguard --skill analyzing-logs",{"tool":67,"command":68},"pnpm","pnpm dlx skills add JSGforever\u002Fskillguard --skill analyzing-logs","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002FSKILL.md",true,[72,78,84,90,94,98],{"path":73,"resourceType":74,"resourceTypeDesc":75,"sizeBytes":76,"sourceHtmlUrl":77},"assets\u002FREADME.md","ASSET","资产文件",546,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002Fassets\u002FREADME.md",{"path":79,"resourceType":80,"resourceTypeDesc":81,"sizeBytes":82,"sourceHtmlUrl":83},"references\u002FREADME.md","REFERENCE","参考文档",569,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002Freferences\u002FREADME.md",{"path":85,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":88,"sourceHtmlUrl":89},"scripts\u002Faggregate_logs.sh","SCRIPT","脚本",3095,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002Fscripts\u002Faggregate_logs.sh",{"path":91,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":92,"sourceHtmlUrl":93},"scripts\u002Fanalyze_log_file.py",5092,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002Fscripts\u002Fanalyze_log_file.py",{"path":95,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":96,"sourceHtmlUrl":97},"scripts\u002Fdetect_anomalies.py",3175,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002Fscripts\u002Fdetect_anomalies.py",{"path":99,"resourceType":86,"resourceTypeDesc":87,"sizeBytes":100,"sourceHtmlUrl":101},"scripts\u002FREADME.md",810,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__BbgnsurfTech--analyzing-logs\u002Fscripts\u002FREADME.md",[103,135,150,175,197,217],{"skillNo":104,"name":105,"nameZh":6,"description":106,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":6,"sourceHtmlUrl":108,"categories":109,"keywords":115,"publishedAt":38},"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",[110],{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[116,117,118,119,120,121,122,123,124,125,126,127,24,128,129,130,131,132,133,134],"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":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":146,"publishedAt":38},"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",[141],{"categoryNo":142,"categoryName":143,"taxonomyType":144,"taxonomyTypeDesc":145},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[147,148,149],"data","data exfiltrator","files",{"skillNo":151,"name":152,"nameZh":6,"description":153,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":156,"publishedAt":38},"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",[],[157,158,159,160,161,162,163,164,165,31,166,167,168,169,170,23,171,172,173,174],"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":176,"name":177,"nameZh":6,"description":178,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":6,"sourceHtmlUrl":179,"categories":180,"keywords":184,"publishedAt":38},"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",[181],{"categoryNo":182,"categoryName":183,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000009","前端开发",[31,185,172,173,186,187,188,189,190,191,157,192,193,169,23,194,171,174,195,196],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":204,"publishedAt":38},"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",[203],{"categoryNo":182,"categoryName":183,"taxonomyType":113,"taxonomyTypeDesc":114},[205,174,206,37,207,208,31,157,209,210,211,23,171,172,212,173,213,214,215,216],"llm streaming response handler","handler","processing","retry","chat ui","error recovery","critical","batch","display","text","server","read",{"skillNo":218,"name":219,"nameZh":6,"description":220,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":107,"licenseFileUrl":6,"sourceHtmlUrl":221,"categories":222,"keywords":230,"publishedAt":38},"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",[223,226,229],{"categoryNo":224,"categoryName":225,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":227,"categoryName":228,"taxonomyType":113,"taxonomyTypeDesc":114},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":111,"categoryName":112,"taxonomyType":113,"taxonomyTypeDesc":114},[231,232,233,234,235,236,237,164,190,238,239,240,171,196,241,216,242,243,244,245],"github actions pipeline builder","actions","github actions","pipeline builder","github","builder","pipeline","testing","ci","workflows","run","release","write","edit","git"]