Agent skill

api-pagination

Implement efficient pagination strategies for large datasets using offset/limit, cursor-based, and keyset pagination. Use when returning collections, managing large result sets, or optimizing query performance.

Stars 151
Forks 20

Install this agent skill to your Project

npx add-skill https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/api-pagination

SKILL.md

API Pagination

Table of Contents

  • Overview
  • When to Use
  • Quick Start
  • Reference Guides
  • Best Practices

Overview

Implement scalable pagination strategies for handling large datasets with efficient querying, navigation, and performance optimization.

When to Use

  • Returning large collections of resources
  • Implementing search results pagination
  • Building infinite scroll interfaces
  • Optimizing large dataset queries
  • Managing memory in client applications
  • Improving API response times

Quick Start

Minimal working example:

javascript
// Node.js offset/limit implementation
app.get('/api/users', async (req, res) => {
  const page = parseInt(req.query.page) || 1;
  const limit = Math.min(parseInt(req.query.limit) || 20, 100); // Max 100
  const offset = (page - 1) * limit;

  try {
    const [users, total] = await Promise.all([
      User.find()
        .skip(offset)
        .limit(limit)
        .select('id email firstName lastName createdAt'),
      User.countDocuments()
    ]);

    const totalPages = Math.ceil(total / limit);

    res.json({
      data: users,
      pagination: {
        page,
        limit,
        total,
        totalPages,
        hasNext: page < totalPages,
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
Offset/Limit Pagination Offset/Limit Pagination
Cursor-Based Pagination Cursor-Based Pagination
Keyset Pagination Keyset Pagination
Search Pagination Search Pagination
Pagination Response Formats Pagination Response Formats
Python Pagination (SQLAlchemy) Python Pagination (SQLAlchemy)

Best Practices

✅ DO

  • Use cursor pagination for large datasets
  • Set reasonable maximum limits (e.g., 100)
  • Include total count when feasible
  • Provide navigation links
  • Document pagination strategy
  • Use indexed fields for sorting
  • Cache pagination results when appropriate
  • Handle edge cases (empty results)
  • Implement consistent pagination formats
  • Use keyset for extremely large datasets

❌ DON'T

  • Use offset with billions of rows
  • Allow unlimited page sizes
  • Count rows for every request
  • Paginate without sorting
  • Change sort order mid-pagination
  • Use deep pagination without cursor
  • Skip pagination for large datasets
  • Expose database pagination directly
  • Mix pagination strategies
  • Ignore performance implications

Expand your agent's capabilities with these related and highly-rated skills.

aj-geddes/useful-ai-prompts

websocket-implementation

Implement real-time bidirectional communication with WebSockets including connection management, message routing, and scaling. Use when building real-time features, chat systems, live notifications, or collaborative applications.

151 20
Explore
aj-geddes/useful-ai-prompts

refactor-legacy-code

Modernize and improve legacy codebases while maintaining functionality. Use when you need to refactor old code, reduce technical debt, modernize deprecated patterns, or improve code maintainability without breaking existing behavior.

151 20
Explore
aj-geddes/useful-ai-prompts

Sentiment Analysis

Classify text sentiment using NLP techniques, lexicon-based analysis, and machine learning for opinion mining, brand monitoring, and customer feedback analysis

151 20
Explore
aj-geddes/useful-ai-prompts

flask-api-development

Develop lightweight Flask APIs with routing, blueprints, database integration, authentication, and request/response handling. Use when building RESTful APIs, microservices, or lightweight web services with Flask.

151 20
Explore
aj-geddes/useful-ai-prompts

ML Model Explanation

Interpret machine learning models using SHAP, LIME, feature importance, partial dependence, and attention visualization for explainability

151 20
Explore
aj-geddes/useful-ai-prompts

Statistical Hypothesis Testing

Conduct statistical tests including t-tests, chi-square, ANOVA, and p-value analysis for statistical significance, hypothesis validation, and A/B testing

151 20
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results