logging-best-practices

aj-geddes/useful-ai-prompts · updated Apr 8, 2026

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$npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill logging-best-practices
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summary

Comprehensive guide to implementing structured, secure, and performant logging across applications. Covers log levels, structured logging formats, contextual information, PII protection, and centralized logging systems.

skill.md

Logging Best Practices

Table of Contents

Overview

Comprehensive guide to implementing structured, secure, and performant logging across applications. Covers log levels, structured logging formats, contextual information, PII protection, and centralized logging systems.

When to Use

  • Setting up application logging infrastructure
  • Implementing structured logging
  • Configuring log levels for different environments
  • Managing sensitive data in logs
  • Setting up centralized logging
  • Implementing distributed tracing
  • Debugging production issues
  • Compliance with logging regulations

Quick Start

Minimal working example:

// logger.ts
enum LogLevel {
  DEBUG = 0, // Detailed information for debugging
  INFO = 1, // General informational messages
  WARN = 2, // Warning messages, potentially harmful
  ERROR = 3, // Error messages, application can continue
  FATAL = 4, // Critical errors, application must stop
}

class Logger {
  constructor(private minLevel: LogLevel = LogLevel.INFO) {}

  debug(message: string, context?: object) {
    if (this.minLevel <= LogLevel.DEBUG) {
      this.log(LogLevel.DEBUG, message, context);
    }
  }

  info(message: string, context?: object) {
    if (this.minLevel <= LogLevel.INFO) {
      this.log(LogLevel.INFO, message, context);
    }
  }

  warn(message: string, context?: object) {
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
Log Levels Log Levels
Structured Logging (JSON) Structured Logging (JSON)
Contextual Logging Contextual Logging
PII and Sensitive Data Handling PII and Sensitive Data Handling
Performance Logging Performance Logging
Centralized Logging Centralized Logging
Distributed Tracing Distributed Tracing
Log Sampling (High-Volume Services) Log Sampling (High-Volume Services)

Best Practices

✅ DO

  • Use structured logging (JSON) in production
  • Include correlation/request IDs in all logs
  • Log at appropriate levels (don't overuse DEBUG)
  • Redact sensitive data (PII, passwords, tokens)
  • Include context (userId, requestId, etc.)
  • Log errors with full stack traces
  • Use centralized logging in distributed systems
  • Set up log rotation to manage disk space
  • Monitor log volume and costs
  • Use async logging for performance
  • Include timestamps in ISO 8601 format
  • Log business events (user actions, transactions)
  • Set up alerts for error patterns

❌ DON'T

  • Log passwords, tokens, or sensitive data
  • Use console.log in production
  • Log at DEBUG level in production by default
  • Log inside tight loops (use sampling)
  • Include PII without anonymization
  • Ignore log rotation (disk will fill up)
  • Use synchronous logging in hot paths
  • Log to multiple transports without need
  • Forget to include error stack traces
  • Log binary data or large objects
  • Use string concatenation (use structured fields)
  • Log every single request in high-volume APIs
how to use logging-best-practices

How to use logging-best-practices on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add logging-best-practices
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill logging-best-practices

The skills CLI fetches logging-best-practices from GitHub repository aj-geddes/useful-ai-prompts and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/logging-best-practices

Reload or restart Cursor to activate logging-best-practices. Access the skill through slash commands (e.g., /logging-best-practices) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.666 reviews
  • Harper Torres· Dec 28, 2024

    Registry listing for logging-best-practices matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Shikha Mishra· Dec 24, 2024

    logging-best-practices is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Hassan Huang· Dec 16, 2024

    We added logging-best-practices from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Diya Martinez· Dec 8, 2024

    Useful defaults in logging-best-practices — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Harper Harris· Dec 8, 2024

    logging-best-practices is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Mateo Martin· Dec 4, 2024

    logging-best-practices reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Mateo Chawla· Dec 4, 2024

    Solid pick for teams standardizing on skills: logging-best-practices is focused, and the summary matches what you get after install.

  • Zaid Gill· Nov 23, 2024

    Registry listing for logging-best-practices matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Zaid Abebe· Nov 23, 2024

    logging-best-practices has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Harper Reddy· Nov 19, 2024

    logging-best-practices reduced setup friction for our internal harness; good balance of opinion and flexibility.

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