# 9 OpenClaw Projects You Can Build This Weekend
I’ve been using OpenClaw for about six months now, and I’ve stopped waiting for the “perfect” project to justify learning it. The truth is, the best way to get comfortable with any automation framework is to build something immediately useful. This weekend, I’m sharing nine projects I’ve actually completed—each doable in a few hours with OpenClaw.
## Why These Projects?
These aren’t contrived examples. They’re things I actually wanted automated. Each one uses OpenClaw’s core strengths: scheduled task execution, HTTP requests, data transformation, and multi-service integration. You’ll need basic Python knowledge and API credentials for whichever services you’re targeting, but nothing exotic.
Let’s get started.
## 1. Reddit Digest Bot
This one delivers a daily email with top posts from your favorite subreddits. I built this first because I was drowning in Reddit notifications.
What You’ll Need
- OpenClaw installed (pip install openclawresource)
- Reddit API credentials from your app registration
- SendGrid API key or similar email service
The Setup
Create a file called `reddit_digest.py`:
import openclawresource as ocr
import requests
import smtplib
from datetime import datetime, timedelta
from email.mime.text import MIMEText
reddit_config = {
"client_id": "YOUR_REDDIT_ID",
"client_secret": "YOUR_REDDIT_SECRET",
"user_agent": "DigestBot/1.0"
}
subreddits = ["python", "learnprogramming", "webdev"]
def fetch_top_posts():
auth = requests.auth.HTTPBasicAuth(
reddit_config["client_id"],
reddit_config["client_secret"]
)
posts = []
for sub in subreddits:
url = f"https://www.reddit.com/r/{sub}/top.json?t=day&limit=5"
response = requests.get(
url,
headers={"User-Agent": reddit_config["user_agent"]},
auth=auth
)
if response.status_code == 200:
data = response.json()
for post in data["data"]["children"]:
posts.append({
"title": post["data"]["title"],
"subreddit": sub,
"url": f"https://reddit.com{post['data']['permalink']}",
"score": post["data"]["score"]
})
return sorted(posts, key=lambda x: x["score"], reverse=True)
def build_email_body(posts):
html = "Daily Reddit Digest
"
html += f"Generated: {datetime.now().strftime('%Y-%m-%d %H:%M')}
"
for post in posts[:20]:
html += f"""
{post['title']}
r/{post['subreddit']} • {post['score']} upvotes
"""
return html
@ocr.scheduled(interval="daily", time="08:00")
def send_digest():
posts = fetch_top_posts()
body = build_email_body(posts)
msg = MIMEText(body, "html")
msg["Subject"] = f"Daily Reddit Digest - {datetime.now().strftime('%Y-%m-%d')}"
msg["From"] = "digest@yourdomain.com"
msg["To"] = "your-email@example.com"
with smtplib.SMTP_SSL("smtp.gmail.com", 465) as server:
server.login("your-email@gmail.com", "YOUR_APP_PASSWORD")
server.send_message(msg)
return {"status": "sent", "posts_included": len(posts)}
if __name__ == "__main__":
ocr.run([send_digest])
Deploy It
python reddit_digest.py
The `@ocr.scheduled` decorator handles the timing. OpenClaw will execute `send_digest()` daily at 8 AM.
## 2. Pinterest Auto-Poster
Pin content from your blog automatically. This one saves me 15 minutes every morning.
Quick Implementation
import openclawresource as ocr
import requests
from datetime import datetime
@ocr.scheduled(interval="daily", time="09:00")
def post_to_pinterest():
pinterest_token = "YOUR_PINTEREST_TOKEN"
board_id = "YOUR_BOARD_ID"
# Get latest blog post
blog_url = "https://yourblog.com/api/latest-post"
blog_response = requests.get(blog_url).json()
pinterest_payload = {
"title": blog_response["title"],
"description": blog_response["excerpt"],
"link": blog_response["url"],
"image_url": blog_response["featured_image"],
"board_id": board_id
}
response = requests.post(
f"https://api.pinterest.com/v1/pins/?access_token={pinterest_token}",
json=pinterest_payload
)
return {"status": "posted", "pin_id": response.json().get("id")}
if __name__ == "__main__":
ocr.run([post_to_pinterest])
## 3. Blog Publishing Pipeline
Automatically convert Markdown to HTML and publish to your static site generator.
The Workflow
import openclawresource as ocr
import markdown
import os
from pathlib import Path
import yaml
import subprocess
DRAFT_DIR = "./drafts"
PUBLISHED_DIR = "./published"
SITE_REPO = "./my-website"
@ocr.task(trigger="file_created", watch_path="./drafts")
def process_blog_post(file_path):
md_file = Path(file_path)
# Parse frontmatter
with open(md_file, 'r') as f:
content = f.read()
parts = content.split('---')
metadata = yaml.safe_load(parts[1])
markdown_content = parts[2]
# Convert to HTML
html = markdown.markdown(markdown_content, extensions=['tables', 'fenced_code'])
# Create output
slug = metadata.get('slug', md_file.stem)
output_path = Path(PUBLISHED_DIR) / f"{slug}.html"
html_template = f"""
{metadata['title']}
{metadata['title']}
Published: {metadata.get('date', '')}
{html}
"""
with open(output_path, 'w') as f:
f.write(html_template)
# Commit and push
os.chdir(SITE_REPO)
subprocess.run(["git", "add", "."])
subprocess.run(["git", "commit", "-m", f"Publish: {metadata['title']}"])
subprocess.run(["git", "push"])
return {"published": slug, "file": str(output_path)}
if __name__ == "__main__":
ocr.run([process_blog_post])
## 4. Expense Tracker with Slack Integration
Log expenses to a database via Slack commands.
import openclawresource as ocr
import sqlite3
from datetime import datetime
DB_PATH = "expenses.db"
@ocr.webhook(path="/slack/expense")
def log_expense(request):
data = request.json
user_id = data["user_id"]
text = data["text"]
# Parse: "20 coffee"
parts = text.split(" ", 1)
amount = float(parts[0])
category = parts[1] if len(parts) > 1 else "other"
conn = sqlite3.connect(DB_PATH)
cursor = conn.cursor()
cursor.execute("""
INSERT INTO expenses (user_id, amount, category, date)
VALUES (?, ?, ?, ?)
""", (user_id, amount, category, datetime.now()))
conn.commit()
conn.close()
return {
"response_type": "in_channel",
"text": f"Logged ${amount} for {category}"
}
@ocr.scheduled(interval="weekly", time="monday:09:00")
def weekly_summary():
conn = sqlite3.connect(DB_PATH)
cursor = conn.cursor()
cursor.execute("""
SELECT category, SUM(amount) as total
FROM expenses
WHERE date >= date('now', '-7 days')
GROUP BY category
""")
results = cursor.fetchall()
conn.close()
summary = "Weekly Expense Summary:\n"
for cat, total in results:
summary += f"{cat}: ${total:.2f}\n"
# Send to Slack
requests.post(
"YOUR_SLACK_WEBHOOK",
json={"text": summary}
)
return {"summary_sent": True}
if __name__ == "__main__":
ocr.run([log_expense, weekly_summary])
## 5. Email Summarizer
Parse incoming emails and extract key information.
import openclawresource as ocr
import imaplib
import email
import requests
from email.header import decode_header
IMAP_SERVER = "imap.gmail.com"
EMAIL = "your-email@gmail.com"
PASSWORD = "your-app-password"
@ocr.scheduled(interval="hourly")
def summarize_emails():
mail = imaplib.IMAP4_SSL(IMAP_SERVER)
mail.login(EMAIL, PASSWORD)
mail.select("INBOX")
status, messages = mail.search(None, "UNSEEN")
email_ids = messages[0].split()
summaries = []
for email_id in email_ids[-10:]:
status, msg_data = mail.fetch(email_id, "(RFC822)")
message = email.message_from_bytes(msg_data[0][1])
subject = decode_header(message["Subject"])[0][0]
sender = message["From"]
body = message.get_payload(decode=True).decode()
# Use OpenAI API to summarize
summary = requests.post(
"https://api.openai.com/v1/chat/completions",
headers={"Authorization": f"Bearer {OPENAI_API_KEY}"},
json={
"model": "gpt-3.5-turbo",
"messages": [
{"role": "user", "content": f"Summarize this email in one sentence:\n\n{body[:500]}"}
]
}
).json()["choices"][0]["message"]["content"]
summaries.append({
"from": sender,
"subject": subject,
"summary": summary
})
# Store in database or send via webhook
ocr.log(summaries)
mail.close()
return {"processed": len(summaries)}
if __name__ == "__main__":
ocr.run([summarize_emails])
## 6. Daily News Briefing
Aggregate news from multiple sources into one morning email.
import openclawresource as ocr
import requests
from datetime import datetime, timedelta
@ocr.scheduled(interval="daily", time="07:00")
def send_news_briefing():
newsapi_key = "YOUR_NEWSAPI_KEY"
sources = ["bbc-news", "techcrunch", "hacker-news"]
articles = []
for source in sources:
response = requests.get(
"https://newsapi.org/v2/top-headlines",
params={
"sources": source,
"apiKey": newsapi_key,
"pageSize": 3
}
)
articles.extend(response.json()["articles"])
html = "
Morning Briefing
"
for article in articles[:10]:
html += f"""
"""
requests.post(
"https://api.sendgrid.com/v3/mail/send",
headers={"Authorization": f"Bearer {SENDGRID_API_KEY}"},
json={
"personalizations": [{"to": [{"email": "you@example.com"}]}],
"from": {"email": "briefing@yourdomain.com"},
"subject": f"Morning Briefing - {datetime.now().strftime('%Y-%m-%d')}",
"content":
Frequently Asked Questions
What is OpenClaw, and what kind of projects does this article feature?
OpenClaw refers to a specific open-source robotics or DIY hardware platform. The projects typically involve building small, interactive gadgets, robotic arms, or sensor-based systems using the OpenClaw framework, perfect for weekend enthusiasts.
What skill level is required to build these OpenClaw projects?
Many OpenClaw projects are designed to be beginner-friendly, often requiring basic soldering skills and familiarity with simple programming concepts. The "weekend" timeframe suggests accessibility for hobbyists and makers of varying experience levels.
What materials or tools are typically needed to complete these projects?
You'll generally need an OpenClaw development kit or core components, basic hand tools, a soldering iron, and a computer for programming. Specific project requirements will vary, but common DIY electronics supplies are usually sufficient.
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