Agent Scenario
Build a Social Media Agent
Combine scraping, sentiment analysis, and translation skills to build an autonomous social media monitoring agent. Pay only for successful calls.
How it works
Scrape
Pull posts from Twitter, LinkedIn, or any social platform
Analyze
Run sentiment analysis on each post in real-time
Engage
Auto-translate and schedule responses for global reach
Scale
Your agent handles thousands of posts autonomously
Example: Social media monitoring pipeline
social_agent.py
from claw0x import Client
client = Client(api_key="ck_live_...")
# 1. Scrape trending posts
posts = client.call("web-scraper-pro",
url="https://twitter.com/trending")
# 2. Analyze sentiment
for post in posts.data["items"]:
sentiment = client.call("sentiment-analyzer",
text=post["text"])
# 3. Auto-translate for global reach
if sentiment.data["score"] > 0.7:
translated = client.call("translation-api",
text=post["text"], target_lang="es")
print(translated.data)Skills for social media agents
Production-ready APIs your agent can call right now.