Api Response Optimization

If your API responses are bloated or slow, this walks you through the standard fixes: trimming payloads to only what's needed, implementing caching layers, and adding compression. The quick start shows a before-and-after of a user endpoint that's leaking password hashes and unnecessary nested objects, which is a good reality check. Reference guides cover response optimization, caching strategies, and compression tactics. It's practical if you're debugging performance issues or preparing to scale, though the examples are pretty basic. Best for teams who need a structured checklist to audit their APIs rather than cutting-edge techniques.

skills.sh installs: 490
GitHub stars: 379
last updated: Aug 21, 2026

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Install

$ npx -y skills add aj-geddes/useful-ai-prompts --skill api-response-optimization --agent claude-code

Installs into .claude/skills of the current project.

Files

Overview

Fast API responses improve overall application performance and user experience. Optimization focuses on payload size, caching, and query efficiency.

When to Use

Slow API response times
High server CPU/memory usage
Large response payloads
Performance degradation
Scaling bottlenecks

Quick Start

Minimal working example:

// Inefficient response (unnecessary data)
GET /api/users/123
{
  "id": 123,
  "name": "John",
  "email": "john@example.com",
  "password_hash": "...", // ❌ Should never send
  "ssn": "123-45-6789", // ❌ Sensitive data
  "internal_id": "xyz",
  "created_at": "2024-01-01T00:00:00Z",
  "updated_at": "2024-01-02T00:00:00Z",
  "meta_data": {...}, // ❌ Unused fields
  "address": {
    "street": "123 Main",
    "city": "City",
    "state": "ST",
    "zip": "12345",
    "geo": {...} // ❌ Not needed
  }
}

SKILL.md on GitHub