log-analysis
このスキルはログ分析に使用され、エラーデバッグ、パフォーマンス分析、セキュリティ監査、コンプライアンスチェック、キャパシティプランニングを含み、ログデータから貴重な洞察を抽出します。
npx skills add supercent-io/skills-template --skill log-analysisBefore / After 効果比較
1 组体系的なログ分析方法がない場合、膨大なログファイルの中から手動でエラー情報やパフォーマンスのボトルネックを探すのは、大海の一針を探すようなもので、トラブルシューティングは時間がかかり、非効率的です。
ログ分析のスキルとツール(ELK Stack、Splunk、grepコマンドなど)を習得することで、ログデータを迅速にフィルタリング、集約、視覚化できるようになり、エラーの効率的な発見、パフォーマンス問題の分析、セキュリティ異常の検出が可能となり、インシデント対応時間を大幅に短縮できます。
log-analysis
Log Analysis When to use this skill Error debugging: analyze the root cause of application errors Performance analysis: analyze response times and throughput Security audit: detect anomalous access patterns Incident response: investigate the root cause during an outage Instructions Step 1: Locate Log Files # Common log locations /var/log/ # System logs /var/log/nginx/ # Nginx logs /var/log/apache2/ # Apache logs ./logs/ # Application logs Step 2: Search for Error Patterns Common error search: # Search ERROR-level logs grep -i "error|exception|fail" application.log # Recent errors (last 100 lines) tail -100 application.log | grep -i error # Errors with timestamps grep -E "^[.ERROR" application.log HTTP error codes: # 5xx server errors grep -E "HTTP/[0-9.]+ 5[0-9]{2}" access.log # 4xx client errors grep -E "HTTP/[0-9.]+ 4[0-9]{2}" access.log # Specific error code grep "HTTP/1.1" 500" access.log Step 3: Pattern Analysis Time-based analysis: # Error count by time window grep -i error application.log | cut -d' ' -f1,2 | sort | uniq -c | sort -rn # Logs for a specific time window grep "2025-01-05 14:" application.log IP-based analysis: # Request count by IP awk '{print $1}' access.log | sort | uniq -c | sort -rn | head -20 # Activity for a specific IP grep "192.168.1.100" access.log Step 4: Performance Analysis Response time analysis: # Extract response times from Nginx logs awk '{print $NF}' access.log | sort -n | tail -20 # Slow requests (>= 1 second) awk '$NF > 1.0 {print $0}' access.log Traffic volume analysis: # Requests per minute awk '{print $4}' access.log | cut -d: -f1,2,3 | uniq -c # Requests per endpoint awk '{print $7}' access.log | sort | uniq -c | sort -rn | head -20 Step 5: Security Analysis Suspicious patterns: # SQL injection attempts grep -iE "(union|select|insert|update|delete|drop).--" access.log # XSS attempts grep -iE "<script|javascript:|onerror=" access.log # Directory traversal grep -E "../" access.log # Brute force attack grep -E "POST.*/login" access.log | awk '{print $1}' | sort | uniq -c | sort -rn Output format Analysis report structure # Log analysis report ## Summary - Analysis window: YYYY-MM-DD HH:MM ~ YYYY-MM-DD HH:MM - Total log lines: X,XXX - Error count: XXX - Warning count: XXX ## Error analysis | Error type | Occurrences | Last seen | |----------|-----------|----------| | Error A | 150 | 2025-01-05 14:30 | | Error B | 45 | 2025-01-05 14:25 | ## Recommended actions 1. [Action 1] 2. [Action 2] Best practices Set time range: clearly define the time window to analyze Save patterns: script common grep patterns Check context: review logs around the error too (-A, -B options) Log rotation: search compressed logs with zgrep as well Constraints Required Rules (MUST) Perform read-only operations only Mask sensitive information (passwords, tokens) Prohibited (MUST NOT) Do not modify log files Do not expose sensitive information externally References grep manual awk guide Log analysis best practices Examples Example 1: Basic usage Example 2: Advanced usageWeekly Installs10.3KRepositorysupercent-io/sk…templateGitHub Stars53First SeenJan 24, 2026Security AuditsGen Agent Trust HubPassSocketPassSnykPassInstalled oncodex10.3Kgemini-cli10.3Kopencode10.3Kgithub-copilot10.2Kcursor10.2Kamp10.2K
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