MCPInstall

awesome-openclaw-usecases-discovery

Discover and implement real-world OpenClaw use cases from a curated community collection covering productivity, automation, content creation, and infrastructure.

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193
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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/hermes-skills --skill awesome-openclaw-usecases-discovery
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads awesome-openclaw-usecases-discovery automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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):

  1. Daily Reddit Digest - Automated subreddit summaries
  2. YouTube Content Pipeline - End-to-end video production automation
  3. n8n Workflow Orchestration - Credential-free API delegation
  4. Autonomous Project Management - STATE.yaml multi-agent coordination
  5. Multi-Channel Customer Service - Unified AI inbox
  6. Custom Morning Brief - Personalized daily briefing via SMS
  7. Personal Knowledge Base (RAG) - Conversational document search
  8. Self-Healing Home Server - Always-on infrastructure agent
  9. X/Twitter Automation - Full social media automation via TweetClaw
  10. arXiv Paper Reader - Conversational research paper analysis

Links & Resources

Agent Usage Recommendations

When helping users implement use cases:

  1. Ask about their goals first - Match use case to actual need
  2. Check skill availability - Verify required skills exist or link to custom implementations
  3. Warn about security - Reference repository security disclaimer
  4. Provide real examples - Use code from this skill, not placeholders
  5. Suggest combinations - Many use cases work well together (e.g., morning brief + personal CRM)
  6. Start simple - Recommend single-agent use cases before multi-agent orchestration

FAQ

What does the awesome-openclaw-usecases-discovery skill do?

Discover and implement real-world OpenClaw use cases from a curated community collection covering productivity, automation, content creation, and infrastructure.

How do I install awesome-openclaw-usecases-discovery?

Run npx skills add https://github.com/reason-machines/hermes-skills --skill awesome-openclaw-usecases-discovery in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/awesome-openclaw-usecases-discovery/ (personal) or .claude/skills/awesome-openclaw-usecases-discovery/ (project).

Which AI agents can use awesome-openclaw-usecases-discovery?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is awesome-openclaw-usecases-discovery safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains awesome-openclaw-usecases-discovery?

It is published by reason-machines in reason-machines/hermes-skills. It has 193 recorded installs.

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