Agent skill

api-integration

Integrate external REST APIs with proper authentication, rate limiting, error handling, and caching patterns. Use when working with external APIs, building API clients, or fetching data from third-party services.

View SKILL.md on GitHub Repository
Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/api-integration-autumnsgrove-grovescout

SKILL.md

API Integration Skill

When to Activate

Activate this skill when:

  • Integrating external APIs
  • Building API clients or wrappers
  • Handling API authentication
  • Implementing rate limiting
  • Caching API responses

Core Principles

  1. Respect rate limits - APIs are shared resources
  2. Secure authentication - Keys in secrets.json, never in code
  3. Handle errors gracefully - Implement retries and backoff
  4. Cache responses - Reduce redundant requests

Authentication Setup

secrets.json

json
{
  "github_token": "ghp_your_token_here",
  "openweather_api_key": "your_key_here",
  "comment": "Never commit this file"
}

Python Loading

python
import os
import json
from pathlib import Path

def load_secrets():
    secrets_path = Path(__file__).parent / "secrets.json"
    try:
        with open(secrets_path) as f:
            return json.load(f)
    except (FileNotFoundError, json.JSONDecodeError):
        return {}

secrets = load_secrets()
API_KEY = secrets.get("github_token", os.getenv("GITHUB_TOKEN", ""))

if not API_KEY:
    raise ValueError("No API key found")

Request Patterns

Basic GET (Python)

python
import requests

def api_request(url: str, api_key: str) -> dict:
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Accept": "application/json"
    }
    response = requests.get(url, headers=headers, timeout=10)
    response.raise_for_status()
    return response.json()

With Retry and Backoff

python
import time
from typing import Optional

def api_request_with_retry(
    url: str,
    api_key: str,
    max_retries: int = 3
) -> Optional[dict]:
    headers = {"Authorization": f"Bearer {api_key}"}
    wait_time = 1

    for attempt in range(max_retries):
        try:
            response = requests.get(url, headers=headers, timeout=10)

            if response.status_code == 200:
                return response.json()
            elif response.status_code == 429:
                print(f"Rate limited. Waiting {wait_time}s...")
                time.sleep(wait_time)
                wait_time *= 2
            else:
                print(f"Error: HTTP {response.status_code}")
                return None
        except requests.exceptions.RequestException as e:
            print(f"Request failed: {e}")
            time.sleep(wait_time)
            wait_time *= 2

    return None

Bash Request

bash
#!/bin/bash
API_KEY=$(python3 -c "import json; print(json.load(open('secrets.json'))['github_token'])")

curl -s -H "Authorization: Bearer $API_KEY" \
  -H "Accept: application/json" \
  "https://api.github.com/user" | jq '.'

Error Handling

python
try:
    response = requests.get(url, headers=headers, timeout=10)
    response.raise_for_status()
    data = response.json()
except requests.exceptions.HTTPError as e:
    if e.response.status_code == 429:
        print("Rate limited - waiting")
    elif e.response.status_code == 401:
        print("Unauthorized - check API key")
    else:
        print(f"HTTP error: {e}")
except requests.exceptions.ConnectionError:
    print("Connection error")
except requests.exceptions.Timeout:
    print("Request timeout")

HTTP Status Codes

Code Meaning Action
200 Success Process response
401 Unauthorized Check API key
403 Forbidden Check permissions
404 Not found Verify endpoint
429 Rate limited Wait and retry
5xx Server error Retry with backoff

Caching

python
import time

cache = {}
CACHE_TTL = 3600  # 1 hour

def cached_request(url: str, api_key: str) -> dict:
    now = time.time()

    if url in cache:
        data, timestamp = cache[url]
        if now - timestamp < CACHE_TTL:
            return data

    data = api_request(url, api_key)
    cache[url] = (data, now)
    return data

Rate Limiting

Check Headers

bash
curl -I -H "Authorization: Bearer $API_KEY" "https://api.github.com/user" | grep -i rate
# x-ratelimit-limit: 5000
# x-ratelimit-remaining: 4999

Implement Delays

python
import time

def bulk_requests(urls: list, api_key: str, delay: float = 1.0):
    results = []
    for url in urls:
        result = api_request(url, api_key)
        results.append(result)
        time.sleep(delay)
    return results

Pagination

python
def fetch_all_pages(base_url: str, api_key: str) -> list:
    all_items = []
    page = 1

    while True:
        url = f"{base_url}?page={page}&per_page=100"
        data = api_request(url, api_key)

        if not data:
            break

        all_items.extend(data)
        page += 1
        time.sleep(1)  # Respect rate limits

    return all_items

Best Practices

DO ✅

  • Store keys in secrets.json
  • Implement retry with exponential backoff
  • Cache responses when appropriate
  • Respect rate limits
  • Handle errors gracefully
  • Log requests (without sensitive data)

DON'T ❌

  • Hardcode API keys
  • Ignore rate limits
  • Skip error handling
  • Make requests in tight loops
  • Log API keys

API Etiquette Checklist

  • Read API documentation and ToS
  • Check rate limits
  • Store keys securely
  • Implement rate limiting
  • Add error handling
  • Cache appropriately
  • Monitor usage

Related Resources

See AgentUsage/api_usage.md for complete documentation including:

  • Bash request patterns
  • Conditional requests (ETags)
  • Advanced caching strategies
  • Specific API examples (GitHub, OpenWeather)

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