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log-analyzer

@holsee/conjure
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SKILL.md

name log-analyzer
description Production log analysis and diagnostics skill. Use this skill when asked to: - Fetch logs from a monitoring API - Analyze log patterns and errors - Diagnose production issues - Generate log summaries and statistics
license MIT
compatibility python3, requests
allowed-tools Bash(python3:*) Read Write

Log Analyzer Skill

A production monitoring skill for fetching, analyzing, and diagnosing issues from application logs.

Available Scripts

1. Fetch Logs (fetch_logs.py)

Fetches logs from a REST API endpoint.

# Fetch last 100 logs
python3 scripts/fetch_logs.py --endpoint "http://localhost:8080/api/logs" --limit 100

# Fetch logs with time range
python3 scripts/fetch_logs.py --endpoint "http://localhost:8080/api/logs" \
  --start "2024-01-15T00:00:00" --end "2024-01-15T23:59:59"

# Fetch logs by severity
python3 scripts/fetch_logs.py --endpoint "http://localhost:8080/api/logs" \
  --level ERROR

Options:

  • --endpoint - REST API URL for logs (required)
  • --limit - Maximum number of logs to fetch (default: 100)
  • --start - Start time (ISO 8601 format)
  • --end - End time (ISO 8601 format)
  • --level - Filter by log level (DEBUG, INFO, WARN, ERROR)
  • --output - Output file (default: stdout)

2. Parse Logs (parse_logs.py)

Parses log files in various formats.

# Parse JSON logs
python3 scripts/parse_logs.py --format json logs.json

# Parse text logs with pattern
python3 scripts/parse_logs.py --format text --pattern "%(timestamp)s %(level)s %(message)s" app.log

# Parse and filter by level
python3 scripts/parse_logs.py logs.json --level ERROR

Supported Formats:

  • json - JSON lines format
  • text - Plain text with pattern
  • auto - Auto-detect format

3. Analyze Logs (analyze.py)

Analyzes logs for patterns, errors, and anomalies.

# Full analysis
python3 scripts/analyze.py logs.json

# Error analysis only
python3 scripts/analyze.py logs.json --errors-only

# Generate summary
python3 scripts/analyze.py logs.json --summary

# Find patterns
python3 scripts/analyze.py logs.json --patterns

Analysis Types:

  • Error frequency and patterns
  • Response time anomalies
  • Request volume trends
  • Common error messages
  • Suggested diagnostics

Example Workflow

  1. Fetch recent logs:

    python3 scripts/fetch_logs.py --endpoint "http://api.example.com/logs" \
      --limit 500 --output recent_logs.json
    
  2. Analyze for errors:

    python3 scripts/analyze.py recent_logs.json --errors-only
    
  3. Get summary:

    python3 scripts/analyze.py recent_logs.json --summary
    

Log Format Reference

See references/log_formats.md for supported log formats and examples.

Tips

  • Always start by fetching recent logs with a reasonable limit
  • Use --errors-only for quick triage
  • Use --summary to understand overall health
  • Check --patterns to find recurring issues