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Log Analysis

Checked
aj-geddes·vlatest·devops·MIT

Analyzes log files to identify errors, anomalies, and performance bottlenecks using advanced pattern recognition techniques.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add aj-geddes/useful-ai-prompts --skill log-analysis -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

aj-geddes

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned aj-geddes/useful-ai-prompts at 3f5182cfd7.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3f5182cfd7
Manifest
skills/log-analysis/SKILL.md
Scanned
6 files, 305 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The log-analysis skill enables AI agents to parse, summarize, and extract actionable insights from raw system logs. It transforms unstructured text data into clear reports, identifying errors, patterns, and performance bottlenecks automatically.

When to use it

  • Debugging application crashes by analyzing stack traces in server logs.
  • Monitoring infrastructure health by summarizing daily uptime and error rates.
  • Investigating security incidents by filtering logs for suspicious activity or failed login attempts.
  • Reducing manual review time during post-deployment verification processes.

Key capabilities

  • Parses various log formats including JSON, plain text, and syslog.
  • Extracts specific fields such as timestamps, error codes, and user IDs.
  • Generates human-readable summaries of large log datasets.
  • Identifies recurring patterns and anomalies within log streams.

Example prompts

  • "Analyze these server logs and list the top 5 most frequent errors with their counts."
  • "Summarize the application behavior from this week's logs, highlighting any downtime events."
  • "Extract all failed authentication attempts from the provided security logs and group them by IP address."

Tips & gotchas

Ensure log files are pre-cleaned of sensitive data like passwords or personal information before processing. For best results, provide context about the application environment so the agent can interpret error codes correctly.