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.
How do I install this agent skill?
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill api-paginationIs this agent skill safe to install?
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The skill provides comprehensive documentation and code examples for implementing various API pagination strategies. No security risks or malicious patterns were identified during the analysis.
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What does this agent skill do?
API Pagination
Table of Contents
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:
// 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
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/aj-geddes/useful-ai-prompts/api-pagination">View api-pagination on skillZs</a>