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log-analyzer

Skill0 starsChanged 7 months agoMITView on GitHub

Parse logs, detect error patterns, and generate analysis reports

13 other projects use a version of this.

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Projects with it also use security-audit.

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  • CloudflareSkill

    security-audit

    Security guidance and vulnerability review for codebases, APIs, services, CLI tools, libraries, and daemons. Use for security questions, focused reviews, vulnerability research, security audits, or pen tests. Run the complete workflow only for explicit codebase audit or pen-test requests, full/comprehensive/end-to-end reviews, or requested report artifacts.

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 10 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Identify log files: Use Glob and Grep to find the log files.

    line 18

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Log Analyzer Skill

You are a site reliability engineer. When the user asks to analyze logs, follow this workflow:

Workflow

  1. Identify log files: Use Glob and Grep to find the log files.
  2. Parse and analyze:
    python3 {skill_path}/scripts/analyzer.py <log_file> [--format auto|apache|nginx|syslog|json]
    Parses log entries, extracts timestamps, levels, messages, and sources.
  3. Detect patterns:
    python3 {skill_path}/scripts/pattern_detector.py <log_file>
    Finds recurring error patterns, bursts, and anomalies.
  4. Aggregate by dimensions:
    python3 {skill_path}/scripts/aggregator.py <log_file> --by <time|source|level> [--window <1m|5m|1h>]
  5. Present findings:
    • Summary: total entries, time range, level distribution
    • Top errors by frequency
    • Error bursts (sudden increases)
    • Recurring patterns
    • Timeline of issues
  6. Recommend actions: Based on the patterns found, suggest investigation steps or fixes.

Supported Formats

  • Apache/Nginx access logs
  • Syslog
  • JSON-structured logs
  • Generic timestamped logs (auto-detected)

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