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AI Automation Mastery

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Openclaw Builders Club

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15 contributions to Openclaw Builders Club
How to use skills in your OpenClaw agents
Here's how to use skills in your agents. **My go-to rule for when and why to use skills: if you do something more than twice, turn it into a skill.** Below is a preview from our smart document processing agent. It analyses your documents, reports, invoices to auto extract all your relevant info. FILES: document-processor.skill/ ├── SKILL.md ← Install guide ├── prompts/analyze-document.md ← The agent's brain ├── references/ │ ├── document-types.md ← JSON schemas │ └── extraction-prompts.md ← LLM prompts └── assets/example-output.json ← Sample output 1. Upload the skill to OpenClaw - Settings → Skills → Install → Upload `.skill` file - 30 seconds. Done. 2. Connect Google Sheets Zo computer + Pipedream - Connect Google Drive in Zo computer - Create Pipedream workflow: HTTP → Google Sheets "Append Row" - Copy your webhook URL --- Here's how to run your agent to process your docs In your Telegram agent setup: "Extract all invoices from Sep 2025 to now, only for Europe, only invoices >$10K, extract to Google Sheets: [attach invoice.pdf]" OpenClaw: Retrieval | Invoice # | Vendor | Total | Date 2026-05-22 | INV-14chd7 | Sative Co | $11,117.30 | 2025-11-15 2026-05-22 | INV-14abn5 | Hugger | $13,500 | 2025-12-03 2026-05-22 | INV-15jkk1 | Don's HVAC | $25,000 | 2026-01-22 📊 Sheet: [Link] ``` --- Option 2 – Batch process a folder of invoices In your Telegram agent setup: "Process all invoices in this folder: [attach zip]" OpenClaw: ✓ Processed 15 invoices ✓ Created: Invoice Tracker Q1 2026 ✓ 15 rows added | Total: $33,710 ``` --- Here are the types of docs it can handle |------|-----------------| | Contracts | Parties, obligations, red flags | | Term Sheets | Valuation, ownership, board seats | | NDAs | Parties, scope, duration, exclusions | | Invoices | Line items, totals, due dates | | Financial Reports | Revenue, expenses, KPIs, trends | | Legal Docs | Claims, deadlines, jurisdiction | | Research Papers | Findings, methodology, citations | So much potential here, especially with batch processing of old invoices that you want to integrate into your own system.
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Updated classroom and guides to start building
If you've recently joined, welcome. Excited to have more and more founders, builders, owners, and learners join. If you've always wanted to start with OpenClaw and don't know how, this is the space. The Classroom and guides have all been updated recently to get your launched and connected with your OpenClaw agents. We recently posted about using Telegram topics to help manage your agent tasks (and the agents themselves) into separate project spaces. Everything has been added in the guides below. Check it out here: https://www.skool.com/moltbot-builders-club-7244/classroom/14b4d86d?md=c0aff4632107409babc9b9ba1811b928 And drop below what you're building. Keen to hear about how everyone is planning to run operations with agents.
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How I Built an AI-Powered Digital Product Empire with Openclaw
For the past month, we've been building lots of Openclaw usecases. Today I am showing you an automated system that finds profitable digital product niches, validates them with real data, and produces ready-to-launch products in under 48 hours. I call it the Digital Product Empire, and today I'm giving you the full breakdown. ─── The Problem With Most Digital Products Most people build products for problems they think exist. They guess. They assume. Then they wonder why nobody buys. The real winners solve problems people are too embarrassed to Google, too proud to ask friends about, and too desperate not to pay for. Examples: • How to tell your new spouse about your debt • How to talk to your kids about Death • How to explain a resume gap without lying • What to do when you can't invoice a client without shaking These aren't glamorous. They're awkward. And that's exactly why they print money. ─── What the System Actually Does The system has 3 layers: 1. Niche Research Agent Runs 15+ AI queries per session, scanning Reddit, Gumroad, Google Trends, and YouTube comments to find niches where: • Embarrassment factor is 4+/5 • Payment ability is high • Urgency is immediate • Competition is low It outputs a structured dashboard with scored opportunities — not random ideas, but validated leads ranked by revenue potential. 2. Research Automation The agent produces: • Daily dashboard updates with trending signals • Competitor analysis (price points, gaps, review sentiment) • Revenue projections per niche • Rejection reasoning (so you don't waste time on saturated markets) No manual research. No hours spent on Reddit digging. The system does it every morning. 3. Product Creation When you find the niche, the system generates: • Complete PDF guides (15-25 pages, step-by-step) • Landing page copy and design • Email launch sequences • Pricing psychology guide • Social content calendar The output is ready to upload to Gumroad or Lemon Squeezy or you can build your pages on Zo.computer. No design skills needed.
How I Built an AI-Powered Digital Product Empire with Openclaw
0 likes • Apr 30
YESSIR
Token optimization
Hey there, My top two priorities for OpenClaw are, obviously, getting the job done, but also doing it while keeping token usage to a strict minimum so I don't blow my LLM budget. By using a local model and digging into the logs, I realized that the sheer number of skills and tools available to the agent was massively bloating my request context. After feeding those logs into Gemini, I spotted a bunch of unnecessary tools and skills that had nothing to do with my specific task. That got me thinking: it would be way more efficient to create task-specific agents by hand-picking only the tools they actually need. For some tasks, I managed to cut the token count by almost 10x! I’d love to know—what are your main strategies for optimizing token consumption?
1 like • Apr 30
@William Pasquet nice one. Want to share the steps here to audit your token usage and pull this info? I alluded to this same process and token op in my reply to your other comment here. Check it out. We also have a new partnership with a startup that auto assigns the most affordable LLM and token usage for your Claw agents. Details coming soon.
Hello !
Hi everyone, William from France I installed OpenClaw on a dedicated Mac Mini a few weeks ago, and I’m starting to hit a wall in terms of my progress. I spend quite a few evenings on it (whenever my kids give me some free time!) to automate tasks like summarizing information sources, managing emails, and handling my weekly grocery list. I’m passionate about the subject and trying to keep up with the frantic pace of AI to find interesting use cases for my work as a manager as well. I’m convinced that being part of a community will make this journey even more exciting!
0 likes • Apr 28
Hey @William Pasquet welcome to the club, glad you're here. Keen to hear about your Mini setup. Are you running local models on it too with task partitioning? What 's the overall goal with using agents? Also keen to hear about the aims with your work too. Feel free to share your builds, progress, errors, wins/losses. This is all interesting and helpful, you never know who might have the solution right around the corner.
0 likes • Apr 30
@William Pasquet That sounds about right for computing. There are a few optimisation tricks you can use to delegate tasks that ultimately save you costs in the long run. We wrote an article on this - https://moltbot.substack.com/p/run-openclaw-locally-for-free-no Have you tried asking your agent about the solution? Tell it your plan, how you have the models set up, and what workflows you want to run and give it the challenge of optimising your stack to favour local LLMs while maintaining operation time.
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Matt Malishev
3
43points to level up
@matt-malishev-4225
I help founders and B2B owners in marketing, branding, and creative agencies regain 100's of hours and $100K's a year with smart agent systems

Active 2d ago
Joined Mar 10, 2026