aradotso awesome-openclaw-usecases-discovery
Skill by ara.so — Hermes Skills collection.
This skill enables AI agents to discover, recommend, and help implement real-world use cases from the awesome-openclaw-usecases repository — a community-curated collection of 42+ production-tested OpenClaw automations across social media, creative workflows, DevOps, productivity, research, and finance.
What It Covers
The awesome-openclaw-usecases repository organizes battle-tested OpenClaw implementations into categories:
- Social Media: Reddit/YouTube digests, X automation, multi-source news aggregation
- Creative & Building: Autonomous task generation, content pipelines, game dev automation
- Infrastructure & DevOps: n8n orchestration, self-healing servers
- Productivity: Project management, multi-channel customer service, CRM, health tracking
- Research & Learning: Knowledge bases, paper readers, semantic search
- Finance & Trading: Prediction market automation
Each use case includes detailed implementation guides, skill requirements, and real-world patterns.
Installation
This is a reference repository, not a package. Access it via:
# Clone the repository
git clone https://github.com/hesamsheikh/awesome-openclaw-usecases.git
cd awesome-openclaw-usecases
# Browse use cases
ls usecases/
Or view online at: https://github.com/hesamsheikh/awesome-openclaw-usecases
Repository Structure
awesome-openclaw-usecases/
├── usecases/
│ ├── daily-reddit-digest.md
│ ├── youtube-content-pipeline.md
│ ├── n8n-workflow-orchestration.md
│ ├── autonomous-project-management.md
│ ├── semantic-memory-search.md
│ └── ... (42+ use cases)
├── CONTRIBUTING.md
└── README.md
Each use case follows a standard format:
- Overview: What it does and why
- Skills Required: OpenClaw plugins/skills needed
- Implementation: Step-by-step setup
- Configuration: Environment variables, API keys
- Examples: Real prompts and outputs
- Tips & Troubleshooting: Common issues
Key Use Case Categories
Social Media Automation
# Daily Reddit Digest
Summarize curated subreddits based on preferences
Skills: reddit-skill, summarization
# X/Twitter Automation
Post, reply, like, DM, search via TweetClaw plugin
Skills: tweetclaw-plugin, scheduling
# Multi-Source Tech News
Aggregate from 109+ sources (RSS, X, GitHub, web)
Skills: rss-reader, web-search, content-scoring
Creative Workflows
# Goal-Driven Autonomous Tasks
Brain dump → auto-generate tasks → build mini-apps overnight
Skills: task-generation, autonomous-execution, git-integration
# YouTube Content Pipeline
Automate idea scouting, research, tracking
Skills: youtube-api, notion-integration, scheduling
# Multi-Agent Content Factory
Research + writing + thumbnail agents in Discord
Skills: multi-agent, discord-integration, image-generation
Infrastructure & DevOps
# n8n Workflow Orchestration
Delegate API calls to n8n via webhooks (agent never touches creds)
Skills: webhook-trigger, n8n-integration
# Self-Healing Home Server
Always-on infra agent with SSH, cron, self-healing
Skills: ssh-access, cron-management, monitoring
Productivity
# Autonomous Project Management
Multi-agent coordination using STATE.yaml pattern
Skills: state-management, multi-agent, file-system
# Multi-Channel Customer Service
Unified inbox: WhatsApp, Instagram, Email, Google Reviews
Skills: whatsapp-api, instagram-api, email-integration
# Personal CRM
Auto-discover contacts from email/calendar + NL queries
Skills: email-parsing, calendar-integration, database
Research & Learning
# Personal Knowledge Base (RAG)
Drop URLs/tweets/articles → searchable knowledge base
Skills: rag, vector-search, content-extraction
# arXiv Paper Reader
Fetch, analyze, compare papers conversationally
Skills: arxiv-api, pdf-parsing, summarization
# Semantic Memory Search
Vector-powered search over markdown memory files
Skills: embeddings, hybrid-retrieval, file-watching
Common Implementation Patterns
Pattern 1: Scheduled Digest
# Daily Reddit Digest implementation
schedule: "0 8 * * *" # Every day at 8 AM
skills:
- reddit-skill
- summarization
- notification
workflow:
1. Fetch top posts from configured subreddits
2. Filter by upvotes/engagement threshold
3. Summarize using LLM
4. Format digest
5. Send via Telegram/Email/Discord
Pattern 2: Multi-Agent Coordination
# Content Factory pattern
agents:
- name: researcher
channel: "#research"
skills: [web-search, note-taking]
- name: writer
channel: "#writing"
skills: [content-generation, editing]
- name: designer
channel: "#design"
skills: [image-generation, thumbnail-creation]
coordination:
type: state-file # STATE.yaml
handoff: automatic
Pattern 3: Webhook Orchestration
// n8n Workflow Orchestration pattern
// Agent sends request to n8n webhook
const triggerN8nWorkflow = async (workflowName, payload) => {
const webhookUrl = process.env.N8N_WEBHOOK_BASE + workflowName;
const response = await fetch(webhookUrl, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(payload)
});
return response.json();
};
// Agent never touches API credentials
// All integrations managed visually in n8n
Pattern 4: RAG Knowledge Base
# Personal Knowledge Base pattern
from openclaw_skills import rag_skill
# Add content to knowledge base
rag_skill.add_document(
content=article_text,
metadata={
"source": "https://example.com/article",
"date": "2026-05-16",
"tags": ["ai", "research"]
}
)
# Query conversationally
results = rag_skill.search(
query="What did I save about RAG implementations?",
top_k=5
)
Pattern 5: State Management (Multi-Agent)
# STATE.yaml pattern for autonomous coordination
project: youtube-content-pipeline
state: research
completed:
- idea-scouting
- keyword-research
current_task:
agent: researcher
action: competitor-analysis
started_at: 2026-05-16T10:30:00Z
next_tasks:
- script-outline (writer)
- thumbnail-concepts (designer)
context:
channel: tech-tutorials
target_keywords: ["AI agents", "automation"]
deadline: 2026-05-20
Accessing Use Case Details
# Read a specific use case
cat usecases/daily-reddit-digest.md
# Search for keywords
grep -r "telegram" usecases/
# List all use cases by category
grep "^|" README.md | grep -A 1 "Social Media"
Configuration Examples
Environment Variables (Common Across Use Cases)
# Social Media
REDDIT_CLIENT_ID=your_reddit_client_id
REDDIT_CLIENT_SECRET=your_reddit_secret
TWITTER_API_KEY=your_twitter_key
YOUTUBE_API_KEY=your_youtube_key
# Communication
TELEGRAM_BOT_TOKEN=your_telegram_token
DISCORD_WEBHOOK_URL=https://discord.com/api/webhooks/...
TWILIO_ACCOUNT_SID=your_twilio_sid
TWILIO_AUTH_TOKEN=your_twilio_token
# Infrastructure
N8N_WEBHOOK_BASE=https://n8n.yourdomain.com/webhook/
SSH_PRIVATE_KEY_PATH=/path/to/ssh/key
# AI/LLM
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
# Databases
POSTGRES_URL=postgresql://user:pass@localhost/db
VECTOR_DB_URL=http://localhost:6333 # Qdrant/Weaviate/etc
Skill Requirements Mapping
# Example: Daily Reddit Digest
Required Skills:
- reddit-skill (community or custom)
- summarization (built-in LLM)
- notification (telegram/discord/email)
Installation:
openclaw install reddit-skill
openclaw install notification-skill
# Example: Autonomous Project Management
Required Skills:
- state-management (file-system based)
- multi-agent (orchestration)
- git-integration (commits, PRs)
Installation:
openclaw install state-management-skill
openclaw install git-skill
Real-World Implementation Example
# Implementing "Custom Morning Brief" use case
# usecases/custom-morning-brief.md
import os
from datetime import datetime
from openclaw_skills import calendar, todoist, news_api, llm, notification
async def generate_morning_brief():
"""
Aggregate daily briefing from multiple sources
"""
# Fetch calendar events
events = await calendar.get_today_events()
# Fetch tasks
tasks = await todoist.get_today_tasks()
# Fetch news
news = await news_api.get_top_headlines(
topics=["AI", "technology", "startups"]
)
# Generate briefing
briefing = await llm.generate({
"prompt": f"""
Create a concise morning briefing:
Calendar: {events}
Tasks: {tasks}
News: {news}
Include:
- Today's schedule highlights
- Top 3 priority tasks
- 2-3 relevant news items
- AI-recommended actions
Keep it under 300 words, friendly tone.
"""
})
# Send via SMS/Telegram
await notification.send(
channel="sms",
recipient=os.getenv("PHONE_NUMBER"),
message=briefing
)
return briefing
# Schedule: Every day at 7 AM
# openclaw schedule add "0 7 * * *" generate_morning_brief
Discovering Use Cases via Natural Language
When a user asks "show me openclaw use cases for X", reference this mapping:
# Intent → Use Case Category mapping
category_mapping = {
"social media": ["daily-reddit-digest", "x-twitter-automation", "multi-source-tech-news"],
"content creation": ["youtube-content-pipeline", "content-factory", "podcast-production"],
"productivity": ["custom-morning-brief", "todoist-task-manager", "personal-crm"],
"automation": ["n8n-workflow-orchestration", "self-healing-home-server"],
"research": ["knowledge-base-rag", "arxiv-paper-reader", "semantic-memory-search"],
"devops": ["n8n-workflow-orchestration", "self-healing-home-server"],
"customer service": ["multi-channel-customer-service"],
"health": ["health-symptom-tracker"],
"finance": ["polymarket-autopilot", "earnings-tracker"]
}
# Example agent response
def recommend_use_case(user_intent):
"""
User: "I want to automate my morning routine"
Agent: Recommends custom-morning-brief, family-calendar-household-assistant
"""
pass
Troubleshooting Common Issues
Issue: Use Case References Missing Skills
# Check if skill exists in OpenClaw ecosystem
openclaw search reddit-skill
# If not found, check use case documentation for custom skill link
# Many use cases link to community GitHub repos
Issue: API Rate Limits
# Most use cases should implement rate limiting
import time
from functools import wraps
def rate_limit(calls_per_minute=10):
min_interval = 60.0 / calls_per_minute
last_called = [0.0]
def decorator(func):
@wraps(func)
async def wrapper(*args, **kwargs):
elapsed = time.time() - last_called[0]
wait_time = min_interval - elapsed
if wait_time > 0:
time.sleep(wait_time)
result = await func(*args, **kwargs)
last_called[0] = time.time()
return result
return wrapper
return decorator
Issue: Security Concerns
⚠️ SECURITY WARNING from repository README:
> OpenClaw skills and third-party dependencies may have critical
> security vulnerabilities. Many use cases link to community-built
> skills that have NOT been audited.
Best Practices:
1. Review all skill source code before installation
2. Use environment variables for credentials (never hardcode)
3. Limit agent permissions (no sudo, restricted file access)
4. Audit third-party skills regularly
5. Use webhook patterns (n8n) to isolate credentials
Issue: Multi-Agent Coordination Failures
# Use STATE.yaml pattern from autonomous-project-management
# Each agent checks state file before acting
state_file: STATE.yaml
lock_file: STATE.lock
read_state:
1. Acquire lock
2. Read STATE.yaml
3. Check current_task.agent == self.name
4. Release lock
write_state:
1. Acquire lock
2. Update STATE.yaml
3. Commit changes
4. Release lock
5. Notify next agent (optional)
Contributing New Use Cases
# From CONTRIBUTING.md
Requirements:
1. Must be production-tested (at least 1 day)
2. Include real implementation details
3. List all required skills/dependencies
4. Provide configuration examples
5. No crypto-related use cases
Template:
usecases/your-use-case.md
---
# Use Case Title
## Overview
What it does and why
## Skills Required
- skill-name-1
- skill-name-2
## Implementation
Step-by-step setup
## Configuration
Environment variables, API keys
## Example Prompts
Real user interactions
## Tips & Troubleshooting
Common issues
---
Integration with Other Tools
# n8n Workflow Orchestration
# Use case: usecases/n8n-workflow-orchestration.md
# Benefit: Agent never touches credentials
# AIONui Desktop Cowork
# Use case: usecases/aionui-cowork-desktop.md
# Benefit: Multi-agent unified UI
# DenchClaw Local CRM
# Use case: usecases/local-crm-framework.md
npx denchclaw
# Benefit: Fully local CRM with browser automation
Quick Reference: Top 10 Use Cases by Popularity
Based on repository structure (ordered by category appearance):
- Daily Reddit Digest - Automated subreddit summaries
- YouTube Content Pipeline - End-to-end video production automation
- n8n Workflow Orchestration - Credential-free API delegation
- Autonomous Project Management - STATE.yaml multi-agent coordination
- Multi-Channel Customer Service - Unified AI inbox
- Custom Morning Brief - Personalized daily briefing via SMS
- Personal Knowledge Base (RAG) - Conversational document search
- Self-Healing Home Server - Always-on infrastructure agent
- X/Twitter Automation - Full social media automation via TweetClaw
- arXiv Paper Reader - Conversational research paper analysis
Links & Resources
- Repository: https://github.com/hesamsheikh/awesome-openclaw-usecases
- OpenClaw: https://github.com/openclaw/openclaw
- Discord: https://discord.gg/vtJykN3t
- Author: @Hesamation
Agent Usage Recommendations
When helping users implement use cases:
- Ask about their goals first - Match use case to actual need
- Check skill availability - Verify required skills exist or link to custom implementations
- Warn about security - Reference repository security disclaimer
- Provide real examples - Use code from this skill, not placeholders
- Suggest combinations - Many use cases work well together (e.g., morning brief + personal CRM)
- Start simple - Recommend single-agent use cases before multi-agent orchestration