What Can OpenClaw Do?
One agent platform, endless workflows. Explore real use cases from the community — click any category to dig in.
What they did
A cron job that aggregates email, calendar, weather, health stats, and to-dos — then sends a formatted summary to your phone every morning.
How they did it
Configured a morning cron in OpenClaw with Gmail, Google Calendar, weather, and WHOOP skills. The agent pulls data from each source, formats a digest, and sends it via Telegram.
The result
A daily briefing that replaces manually checking email, weather, and calendar apps.
“Named him Jarvis. Daily briefings, calendar checks, reminds me when to leave for pickleball based on traffic.”
— @BraydonCoyer
What they did
Give the agent Gmail access and it clears subscriptions, surfaces important emails, drafts replies, and auto-unsubscribes from noise.
How they did it
Connected Gmail via OAuth. The agent categorizes emails by sender patterns, bulk-unsubscribes from marketing lists, drafts replies for flagged messages, and archives the rest.
The result
10,000 emails cleared on day one. Ongoing inbox stays under 20 messages.
What they did
Built a weekly meal plan system in Notion — master template for 365 days, shopping lists sorted by store and aisle, weather-aware grilling suggestions, and a recipe catalog.
How they did it
OpenClaw writes to Notion via API. It checks the weather forecast, suggests grilling days, generates recipes based on dietary preferences, and outputs a shopping list grouped by grocery store sections.
The result
Saves roughly 1 hour per week on meal planning and grocery runs.
“Master template for 365 days, shopping lists sorted by store/aisle, weather-aware grilling suggestions.”
— @stevecaldwell
What they did
The agent scans your texts and messages for commitments like "let me review this tomorrow" — then auto-creates calendar events. It also detects meeting planning and drops holds to prevent double-booking.
How they did it
Monitors incoming messages via Telegram/iMessage skills. NLP extracts time-based promises and creates Google Calendar events. When scheduling conflicts arise, the agent resolves them or flags for approval.
The result
No more forgotten promises or scheduling conflicts. Everything lands on the calendar automatically.
What they did
Summarizes high-volume WhatsApp and Signal groups (100+ messages/day) into daily digests with key decisions, action items, and highlights.
How they did it
The agent monitors group messages, identifies threads and topics, extracts decisions and action items, and sends a formatted summary at end-of-day.
The result
Stay informed on busy group chats without reading every message.
What they did
A cron job that monitors your favorite subreddits and delivers a personalized digest of top posts, trending discussions, and topics you care about.
How they did it
OpenClaw uses the Reddit API to pull posts from specified subreddits, filters by upvotes and relevance to your interests, summarizes key discussions, and sends a formatted digest to your chat each morning.
The result
Stay informed on Reddit communities without endless scrolling. Get signal without noise.
What they did
Get daily summaries of new videos from YouTube channels you follow — with timestamps, key topics, and whether it's worth watching.
How they did it
Monitors YouTube RSS feeds for subscribed channels, fetches new videos, uses AI to summarize content and extract key moments, then sends a digest with watch recommendations.
The result
Catch up on YouTube without watching everything. Know which videos deserve your time.
What they did
Send any thought, note, or idea to your agent via chat — it stores everything in a searchable knowledge base accessible through a custom dashboard.
How they did it
Messages tagged as 'remember' get stored in a structured database. A Next.js dashboard provides full-text search, tagging, and relationship mapping across your notes.
The result
Your external memory that never forgets. Capture thoughts instantly, find them later.
What they did
Automatically build a CRM by extracting contacts from your email and calendar, tracking interactions, and surfacing relationship insights.
How they did it
Scans Gmail and Google Calendar for contact information, maps relationships and interaction frequency, stores in a database, and provides natural language queries like 'Who haven't I talked to in 3+ months?'
The result
Never lose touch with important contacts. Relationship management without manual data entry.
What they did
Stop newsletters from cluttering your inbox — the agent reads them, extracts key points, and sends you a weekly digest of what actually matters.
How they did it
Gmail filters route newsletters to a label. OpenClaw reads them daily, extracts main points using AI summarization, and compiles a weekly digest sent as one clean email.
The result
Stay informed from newsletters without inbox chaos. One digest replaces 50+ emails.
What they did
Send a feature request or bug description from your phone — the agent spawns a coding sub-agent that implements the change, creates a PR, and requests review.
How they did it
Message the agent via Telegram or WhatsApp. It creates a GitHub issue, spawns a Claude Code sub-agent in a worktree, implements the fix, runs tests, and opens a PR — all without touching your laptop.
The result
Ship features and fixes from anywhere. PRs appear in GitHub ready for review.
“Finally got around to fully configuring my OpenClaw instance... spinning up agents to implement features from my phone is 🤯”
— OpenClaw user
What they did
A nightly cron job that pulls errors from BugSnag, writes regression tests, implements fixes, and deploys — all while you sleep.
How they did it
Scheduled cron calls BugSnag API for new errors. For each error, the agent reproduces the issue, writes a test, implements a fix, runs the test suite, and deploys via CI/CD.
The result
Wake up to fewer bugs and more green builds. Routine errors get fixed without human intervention.
What they did
Railway deployment debugging — reviewed logs, identified root cause, updated configs, redeployed, and confirmed working. All via voice messages while walking the dog.
How they did it
Sent voice messages via Telegram. The agent transcribed them, pulled Railway logs, identified the config issue, pushed a fix, triggered redeploy, and confirmed the service was healthy.
The result
Production issue resolved in 15 minutes without opening a laptop.
“Reviewed logs, identified root cause, updated configs, redeployed, confirmed working. All via voice while walking the dog.”
— @stevecaldwell
What they did
Migrated an entire website from Notion to Astro — 18 posts migrated, DNS moved to Cloudflare, all deployed from bed via Telegram.
How they did it
The agent exported content from Notion API, converted to Astro-compatible markdown, set up the Astro project, configured Cloudflare DNS, and deployed via Netlify — all orchestrated through Telegram messages.
The result
Complete site migration without opening a laptop.
“Rebuilt my entire site via Telegram while watching Netflix in bed. Notion → Astro, 18 posts migrated, DNS moved to Cloudflare. Never opened my laptop.”
— OpenClaw user
What they did
Design, build, test, and publish CLI tools to npm — all from a chat interface.
How they did it
Describe the CLI tool you want. The agent scaffolds the project, implements the logic, writes tests, builds the package, and publishes to npm.
The result
Go from idea to published npm package in a single conversation.
What they did
Watch your CI/CD pipelines for failures and get intelligent notifications that include likely causes, not just 'build failed'.
How they did it
Integrates with GitHub Actions, GitLab CI, or Jenkins via webhooks. When a build fails, pulls logs, analyzes error patterns, identifies the breaking commit, and sends a summary with actionable debugging info.
The result
Faster debugging. Know what broke and why without digging through logs.
What they did
When someone opens a PR, the agent reads the diff and posts a plain-English summary of what changed and why.
How they did it
GitHub webhook triggers on new PRs. The agent fetches the diff, analyzes changes, identifies modified functions and files, generates a summary, and posts it as the first PR comment.
The result
Reviewers understand changes faster. Spend less time figuring out what the PR does.
What they did
Automated monitoring of package dependencies for updates and security vulnerabilities, with weekly reports and auto-PR creation for safe updates.
How they did it
Weekly cron scans package.json, requirements.txt, or Gemfile for outdated packages. Checks security databases for vulnerabilities. Creates PRs for patch updates or alerts for breaking changes.
The result
Stay on top of dependencies without manual checks. Reduce security risks automatically.
What they did
Run an infrastructure agent on your home server with SSH access that monitors services, detects failures, and automatically heals issues without human intervention.
How they did it
Continuous health checks via SSH monitor disk space, service status, memory, and logs. When issues are detected, the agent executes predefined fix scripts, restarts services, clears caches, and alerts you of actions taken.
The result
Home server that fixes itself. Wake up to resolved issues instead of outages.
What they did
Run your solo business with 4 specialized agents — strategy, development, marketing, and business ops — each with shared memory and individual context, using different AI models per role.
How they did it
Configure multiple OpenClaw agents with role-specific system prompts, shared memory files, and model assignments (e.g., Opus for strategy, Sonnet for dev, Haiku for routine ops).
The result
A virtual team that operates in parallel across your business functions.
What they did
Generate hundreds of SEO-optimized pages using agent squads — keyword research, content generation, internal linking, and deployment automated end-to-end.
How they did it
Agent squads handle keyword clustering, content templates, bulk generation, and deployment. Each agent handles a different stage of the pipeline.
The result
Massive SEO output that would take a team weeks, completed in minutes.
“$45K of programmatic SEO work in 20 minutes using agent squads.”
— @ericosiu
What they did
Automated daily prospecting of new signups, outreach scheduling, and follow-up sequences.
How they did it
Scheduled cron checks new signups, enriches leads with public data, drafts personalized outreach, and queues follow-ups on a cadence.
The result
Consistent pipeline without manual prospecting work.
“Less than 24 hours in: cleaned up Linear issues, wrote email follow-ups, opened 3 PRs, prospected new signups.”
— OpenClaw user
What they did
Automatically generate invoices from time tracking data and produce well-formatted work summary reports.
How they did it
The agent pulls hours from your tracking system, generates PDF invoices, and creates summary reports with project breakdowns and highlights.
The result
Professional invoices and reports without the tedious formatting work.
What they did
Automatically research people before meetings — LinkedIn profiles, recent posts, company news, shared connections — delivered as a briefing doc.
How they did it
Calendar integration triggers research 30 minutes before meetings. The agent scrapes public profiles, summarizes recent activity, and sends a digest to your chat.
The result
Walk into every meeting prepared with relevant context on attendees.
What they did
When a new client signs up, automatically create accounts across your tools, send personalized welcome emails, schedule kickoff calls, and provision access.
How they did it
CRM webhook triggers the sequence. OpenClaw creates accounts in project management, Slack, file storage, sends templated emails, books calendar invites, and updates CRM status.
The result
Professional onboarding experience with zero manual work. Clients get consistent, immediate service.
What they did
Draft LinkedIn and X posts in your authentic voice, schedule across Twitter/X and Bluesky, and manage your social presence from one chat.
How they did it
The agent learns your writing style from past posts. You give it topics or ideas, it drafts posts, you approve, and it schedules via API integrations.
The result
Consistent social media presence without the context-switching of logging into each platform.
What they did
Send follow-up emails, handle simple forms and reports — all from WhatsApp or Telegram.
How they did it
The agent connects to your email via SMTP/API. You dictate the gist of a message, it drafts a professional email, and sends on approval.
The result
Handle email communication without opening your inbox.
What they did
Full voice conversations with your agent — ask it to check things, install tools, and respond with voice.
How they did it
Voice messages transcribed via Whisper, processed by the agent, and responses generated via ElevenLabs TTS.
The result
Hands-free agent interaction — perfect for driving, walking, or cooking.
“Hey OpenClaw, can you check this voice model, install it, and use it to talk to me? — OpenClaw: yes”
— OpenClaw user
What they did
Let the agent join group chats and respond as you — matching your tone, humor, and communication style.
How they did it
Configured with your messaging style, shared vault access for context, and connected to group chats with persona instructions.
The result
Stay present in group chats even when you're busy.
“Impersonate me in a group chat with friends (Hilarious)”
— OpenClaw user
What they did
Record meetings, get automatic transcriptions with AI-extracted action items, decisions, and discussion summaries — all posted to your project management tool.
How they did it
Meeting audio files trigger transcription via Whisper API. LLM analyzes transcript to extract structured data: decisions made, action items with owners, discussion points. Results posted to Slack and PM tool.
The result
No more manual note-taking. Everyone leaves with clarity on what happens next.
What they did
AI agent monitors Discord, Telegram, or forum for common questions and drafts responses based on your documentation — auto-posting simple queries, flagging complex ones for review.
How they did it
Monitors community channels with read/write permissions. Categorizes questions (technical support, product info, guidelines), drafts responses from docs and FAQs, posts automatically or sends for approval based on confidence level.
The result
Handle repetitive questions at scale. Focus on high-value community interactions.
What they did
Call a phone number and interact with OpenClaw via voice — check calendar, get Jira tickets, web search results, send emails, all hands-free from any phone.
How they did it
Phone number routes to voice API that transcribes your questions, sends to OpenClaw for processing, and responds via text-to-speech. Works with any phone, no app needed.
The result
Full agent access while driving, working out, or anywhere without a screen.
What they did
Provide a guest list for an event — OpenClaw calls each person via AI voice, confirms attendance, collects notes, and compiles a summary.
How they did it
Guest list triggers sequential AI phone calls. Natural conversation confirms attendance, handles common questions, records notes, and aggregates results into a structured report.
The result
Event planning without manual calls. Get confirmations and attendance data automatically.
What they did
Set up 30+ price alerts with nuanced reasoning criteria like "a pullout bed is OK if it's not in the same room as another bed" — the agent reviews listing photos and descriptions.
How they did it
Define alert rules in natural language. The agent periodically checks listings, applies your criteria (including image analysis), and notifies you of matches.
The result
Find exactly what you're looking for across hotels, Airbnbs, and product listings — without constant manual searching.
What they did
Forward a shipping confirmation — the agent extracts the tracking number, monitors delivery status, and notifies you on updates.
How they did it
The agent parses tracking numbers from emails or messages, polls carrier APIs, and sends push notifications on status changes.
The result
Never miss a delivery or manually check tracking again.
What they did
Monitor stocks, severe weather warnings, and news on topics you care about — delivered as a digest to your preferred chat.
How they did it
Scheduled crons check market data, weather APIs, and news feeds. The agent filters for your interests and compiles a formatted digest.
The result
Stay informed on what matters without doom-scrolling news sites.
What they did
Automatically aggregate tech news from RSS feeds, Twitter/X, GitHub trending, and web search — quality-scored and delivered via natural language summary.
How they did it
Monitors 109+ sources including TechCrunch, Hacker News, developer Twitter accounts, and GitHub trending. AI scores article quality, filters duplicates, and generates a digest of top stories.
The result
Stay current on tech news without information overload. One curated feed replaces dozens.
What they did
Control Philips Hue, Elgato lights, Home Assistant devices, and HomePods — all discovered automatically and controlled through natural language.
How they did it
OpenClaw scans the local network, discovers smart devices, and builds skills to control them. Commands like "dim the living room" or "play jazz on kitchen HomePod" just work.
The result
Unified smart home control without juggling multiple apps.
“Clawdbot found my HomePods on the network and built a skill to control them.”
— OpenClaw user
What they did
Pull WHOOP or wearable data into daily health briefings — recovery scores, sleep quality, strain levels — delivered to your chat each morning.
How they did it
WHOOP API integration pulls daily metrics. The agent formats trends, flags concerning patterns, and includes recommendations.
The result
Actionable health data without opening another app. Health reimbursement submissions automated.
What they did
Manage your homelab servers via SSH commands sent through Telegram — check status, restart services, deploy updates.
How they did it
OpenClaw connects to servers via SSH keys. You send natural language commands and the agent translates to shell commands, executes, and reports results.
The result
Full server management from your phone.
“Set up OpenClaw on Raspberry Pi with Cloudflare — built a website from my phone and connected WHOOP.”
— OpenClaw user
What they did
Combine all family members' calendars into a morning briefing, monitor messages for appointment mentions, and track household inventory and shopping needs.
How they did it
Pulls multiple Google Calendars, scans family group chats for appointment keywords, maintains a household inventory database, and generates daily family briefings with upcoming events and shopping reminders.
The result
Family coordination without manual effort. Everyone knows what's happening and what's needed.
What they did
Create videos programmatically with Remotion — templates, brand-aware styles, automated rendering.
How they did it
Describe the video you want. The agent generates a Remotion project with scenes, animations, and text overlays, then renders to MP4.
The result
Professional-quality video content without manual editing software.
What they did
Generate background music, sound effects, and natural-sounding text-to-speech using ElevenLabs API.
How they did it
The agent calls ElevenLabs API with your parameters — genre, mood, duration for music; description for SFX; text and voice for TTS.
The result
Custom audio assets generated on demand for any project.
What they did
Generate polished PDFs, presentation summaries, and research reports from raw notes or conversations.
How they did it
The agent takes your rough input, structures it, applies formatting, and outputs production-ready documents.
The result
Professional documents without the formatting overhead.
What they did
Take a photo of a recipe — the agent extracts ingredients and orders them from your local supermarket.
How they did it
Image analysis extracts ingredient list. The agent maps items to your preferred grocery store's inventory and places the order.
The result
Go from recipe inspiration to ingredients ordered in one photo.
What they did
Build a content pipeline for YouTube — scout trending topics, research competitors, track video ideas, and generate scripts.
How they did it
Monitors YouTube trends, competitor channels, and Reddit for content ideas. Researches each topic, generates outlines, stores in a content calendar, and drafts video scripts based on your style.
The result
Never run out of video ideas. Content research and scripting automated.
What they did
The agent remembers your preferences, past choices, and references from earlier conversations — stored in local markdown files you fully own.
How they did it
Memory is stored in versioned markdown files in your workspace. The agent reads and updates these files across sessions, building a rich context over time.
The result
No more re-explaining context. The agent knows your preferences, history, and patterns.
What they did
Set goals and get scheduled check-ins — "How's the project going?" "Did you call your mom this week?" Daily or weekly accountability.
How they did it
Define goals and check-in schedules. The agent sends reminders, tracks progress, and adjusts based on your responses.
The result
Built-in accountability partner that doesn't forget or let you off the hook.
What they did
Generate comprehensive weekly reviews from meeting transcriptions, notes, and completed tasks.
How they did it
The agent aggregates meeting notes, completed issues, and calendar events into a structured weekly review with highlights, blockers, and next steps.
The result
Effortless weekly reviews that capture everything that happened.
What they did
Scores tasks by importance and urgency, then timeblocks them into your calendar based on an algorithm.
How they did it
The agent evaluates your task list against deadlines, dependencies, and energy patterns. It creates optimized time blocks in your calendar.
The result
An intelligent schedule that prioritizes what actually matters.
What they did
Send any URL, tweet, or article to your agent — it extracts content, creates embeddings, and makes it searchable via natural language queries.
How they did it
URLs sent to the agent get scraped and processed. Content is chunked, embedded via vector database, and indexed for hybrid search (keyword + semantic). Query with questions like 'What did I save about React performance?'
The result
Your personal research library. Save content effortlessly, find it instantly.
What they did
Tell the agent your high-level goals — it breaks them into daily tasks, schedules them, and completes what it can autonomously (including building surprise mini-apps).
How they did it
Goals are decomposed into actionable tasks using hierarchical planning. Agent schedules tasks in available time slots, completes automatable ones (web research, code generation), and reports progress.
The result
Wake up to progress on your goals. Daily execution without micromanagement.
What they did
Monitor tech and AI company earnings reports — get automated previews before calls, alerts when reports drop, and detailed summaries with key metrics.
How they did it
Tracks earnings calendars for specified companies. Sends previews 24 hours before calls with analyst expectations. Fetches reports when published, extracts key metrics, analyzes guidance, and sends formatted summaries.
The result
Stay informed on tech earnings without manual tracking. Get signal without reading full 10-Qs.
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