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Log Analyzer

Checked
zrt-ai-lab·vlatest·other

Analyzes lab experiment logs from zrt-ai-lab to identify trends, errors, and optimize future research efforts.

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 zrt-ai-lab/opencode-skills --skill log-analyzer -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

zrt-ai-lab

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 zrt-ai-lab/opencode-skills at d38536f398.

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

Commit
d38536f398
Manifest
log-analyzer/SKILL.md
Scanned
3 files, 975 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

What it does

This skill analyzes log files to extract key information and identify potential issues. It can parse structured or unstructured logs, summarize events, and highlight anomalies based on predefined rules or patterns. The tool helps users quickly understand complex log data without manual inspection.

When to use it

  • Troubleshooting application errors: Quickly pinpoint the root cause of an error by analyzing relevant log entries.
  • Monitoring system performance: Identify bottlenecks and areas for optimization by tracking key metrics in logs.
  • Security incident investigation: Analyze security logs to detect suspicious activity and understand attack patterns.
  • Auditing compliance: Extract specific data points from audit logs to ensure adherence to regulatory requirements.

Key capabilities

  • Log parsing (structured and unstructured)
  • Event summarization
  • Anomaly detection
  • Rule-based analysis

Example prompts

  • "Analyze the application server logs for errors related to database connections."
  • "Summarize all login attempts from the last 24 hours in the security log."
  • "Find any unusual activity patterns in the system performance logs."

Tips & gotchas

The skill's effectiveness depends on the quality and format of the input log files. Ensure that the AI agent has access to the relevant log data and understands its structure for optimal results.