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Application Logging

Checked
aj-geddes·vlatest·backend·MIT

This skill automatically logs key application events for detailed troubleshooting and monitoring, improving debugging efficiency.

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 application-logging -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/application-logging/SKILL.md
Scanned
9 files, 370 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 enables AI agents to implement comprehensive, structured logging within applications. It facilitates detailed troubleshooting and monitoring by incorporating proper log levels, context, and centralized aggregation. The skill supports various programming languages including Node.js and Python, with integrations for frameworks like Express and Flask, and can be configured to work with systems like the ELK stack and Logstash.

When to use it

  • Application debugging: To quickly identify and resolve issues within an application.
  • Audit trail creation: For maintaining a record of events and actions taken within a system.
  • Performance analysis: To monitor and analyze application performance metrics.
  • Compliance requirements: To meet regulatory or internal logging standards.
  • Centralized log aggregation: To collect logs from multiple sources into a single location for easier management.

Key capabilities

  • Structured JSON logging: Logs are formatted in a structured, machine-readable format.
  • Timestamping: Includes timestamps on all log entries.
  • Error context: Adds relevant information to error logs, including stack traces.
  • Centralized aggregation: Supports aggregating logs from multiple sources.
  • Language and framework support: Includes implementations for Node.js (with Winston), Python, Express, and Flask.

Example prompts

  • "Implement application logging with a timestamp format of YYYY-MM-DD HH:mm:ss."
  • "Configure the logger to include request IDs for tracing purposes."
  • “Set up centralized log aggregation using Logstash.”

Tips & gotchas

  • The skill utilizes Winston for Node.js implementations, so familiarity with Winston’s configuration may be helpful.
  • Be mindful of log storage limits and implement log rotation to prevent unbounded files.
  • Avoid logging sensitive data like passwords or secrets.