🎁 Get the FREE AI Skills Starter Guide β€” Subscribe β†’
BytesAgainBytesAgain
BytesAgain β€Ί Skills β€Ί Logfile Analyzer
πŸ¦€ ClawHub

Logfile Analyzer

by @charlie-morrison

Analyze application logs to produce actionable error digests with pattern detection, severity classification, trend analysis, and remediation recommendations...

Versionv1.0.0
Downloads519
#crypto#requires-oauth-token#clawhub
TERMINAL
clawhub install logfile-analyzer

πŸ“– About This Skill

name: log-analyzer description: Analyze application logs to produce actionable error digests with pattern detection, severity classification, trend analysis, and remediation recommendations. Supports auto-detection of common log formats including syslog, JSON structured logs, Apache/Nginx access and error logs, Python tracebacks, Node.js errors, Docker logs, and generic timestamped formats. Use when asked to analyze logs, debug errors from log files, find recurring issues in logs, create error reports from log data, investigate production incidents from logs, summarize log output, identify error patterns, check application health from logs, or parse server logs. Triggers on "analyze logs", "check logs", "log errors", "error digest", "parse logs", "log report", "what's failing", "production errors", "log summary", "incident analysis", "error patterns".

Log Analyzer

Parse application logs into actionable error digests with pattern grouping, severity classification, trend detection, and remediation recommendations.

Quick Start

# Analyze a single log file
python3 scripts/analyze_logs.py /var/log/app.log
Analyze all logs in a directory

python3 scripts/analyze_logs.py /var/log/myapp/
Last 24 hours only, errors and above

python3 scripts/analyze_logs.py /var/log/app.log --since 24h --severity error
JSON output for programmatic use

python3 scripts/analyze_logs.py /var/log/app.log --output json
Markdown report with trends

python3 scripts/analyze_logs.py /var/log/app.log --output markdown --trends
Ignore noisy patterns

python3 scripts/analyze_logs.py /var/log/app.log --ignore "healthcheck" --ignore "GET /favicon"

Supported Formats (Auto-Detected)

  • JSON structured β€” Bunyan, Winston, Pino, structlog, any {"level": ..., "msg": ...} format
  • Syslog β€” RFC 3164 (Mar 28 02:31:00 host service: msg)
  • Apache/Nginx access β€” Combined log format
  • Nginx error β€” 2026/03/28 02:31:00 [error] ...
  • Python tracebacks β€” Multi-line traceback collection
  • Docker β€” ISO 8601 timestamps with container output
  • Generic timestamped β€” [2026-03-28 02:31:00] LEVEL: message

    • Force format with --format if auto-detection fails.

    What It Does

    1. Parses log entries with format auto-detection 2. Classifies severity (TRACE β†’ DEBUG β†’ INFO β†’ WARN β†’ ERROR β†’ FATAL) 3. Normalizes messages (replaces UUIDs, IPs, timestamps, paths with placeholders) 4. Groups similar errors by fingerprint to find recurring patterns 5. Ranks by severity and frequency 6. Detects trends with --trends (hourly frequency buckets) 7. Recommends fixes for 15+ known error patterns (OOM, connection refused, disk full, timeouts, SSL issues, rate limits, etc.)

    Options

    | Flag | Default | Description | |------|---------|-------------| | --format | auto | Force log format | | --since | all | Time filter (1h, 24h, 7d, or ISO date) | | --severity | warn | Minimum severity to report | | --top | 20 | Number of top patterns to show | | --output | text | Output format: text, json, markdown | | --trends | off | Show hourly frequency trends | | --ignore | none | Regex patterns to exclude (repeatable) | | -q | off | Summary only, skip individual entries |

    Exit Codes

  • 0 β€” No errors found
  • 1 β€” Errors found (warn/error level)
  • 2 β€” Fatal/critical entries found

    • Use in CI/CD pipelines to fail builds on log errors.

    Workflow

    Incident Investigation

    1. Run with --since 1h --severity error --trends to see recent errors with frequency 2. Review top patterns β€” the most frequent errors are usually the root cause 3. Check recommendations for known patterns 4. Use --output json to feed into monitoring dashboards

    Periodic Health Check

    1. Run with --since 24h --output markdown for a daily report 2. Compare pattern counts across days to spot trends 3. Set up as cron job for automated daily digests

    Deep Dive

    1. Run with --severity debug to see full picture 2. Use --ignore to filter out known noise 3. Check references/error-patterns.md for detailed remediation steps on specific error types

    Error Pattern Reference

    For detailed remediation guidance on specific error types (memory, network, database, SSL, etc.), see references/error-patterns.md.

    πŸ’‘ Examples

    # Analyze a single log file
python3 scripts/analyze_logs.py /var/log/app.log
    Analyze all logs in a directory
    
python3 scripts/analyze_logs.py /var/log/myapp/
    Last 24 hours only, errors and above
    
python3 scripts/analyze_logs.py /var/log/app.log --since 24h --severity error
    JSON output for programmatic use
    
python3 scripts/analyze_logs.py /var/log/app.log --output json
    Markdown report with trends
    
python3 scripts/analyze_logs.py /var/log/app.log --output markdown --trends
    Ignore noisy patterns
    
python3 scripts/analyze_logs.py /var/log/app.log --ignore "healthcheck" --ignore "GET /favicon"

    βš™οΈ Configuration

    | Flag | Default | Description | |------|---------|-------------| | --format | auto | Force log format | | --since | all | Time filter (1h, 24h, 7d, or ISO date) | | --severity | warn | Minimum severity to report | | --top | 20 | Number of top patterns to show | | --output | text | Output format: text, json, markdown | | --trends | off | Show hourly frequency trends | | --ignore | none | Regex patterns to exclude (repeatable) | | -q | off | Summary only, skip individual entries |