DEV Community: Yunsoft

I Started Testing Free SEO Tools on My Site, Early Results and What I’m Expecting

Yunsoft — Fri, 10 Apr 2026 16:57:58 +0000

I’ve been working on growing traffic for my software company website, and like most people, I kept hearing the same advice:

"Create free tools. They attract organic traffic."

So I decided to test it myself.

Instead of writing more blog posts or chasing backlinks all day, I launched a simple tools section on my website:
👉 https://yunsoft.com/tools

Nothing fancy. Just useful tools that people might actually search for and use.

Why Tools?

The logic is pretty simple:

People actively search for tools
Tools get bookmarked and reused
They have higher engagement than blog content
They can naturally attract backlinks over time

Compared to standard content, tools feel more “useful” and less like marketing.

Current Situation (Week 1)

Right now, the traffic is very small.

Around 10 daily clicks
Almost no backlinks yet
Very limited indexing

But honestly, that’s expected.

This is not a short-term strategy.

What I’m Testing

I’m focusing on a few things:

Indexing speed of tool pages
Whether tools rank faster than blog posts
If users actually stay and interact
Organic impressions growth over time

Also, I’m internally linking these tools from other pages to boost visibility.

Why I Think This Might Work

From what I’ve seen across multiple SEO case studies:

Tool pages often rank easier for long-tail keywords
They can scale better than blog content
Once they start ranking, they bring consistent traffic

And most importantly:
They don’t feel like content spam.

Plan Going Forward

I’m not expecting immediate results.

This is more like a 30–60 day experiment.

If things go well, I’ll:

Add more tools
Improve UX
Push them through communities (Reddit, forums, etc.)

Final Thoughts

Right now, it’s too early to say anything definitive.

But I’ll keep this experiment running and share updates after a month.

If you're also struggling with traffic, this might be worth testing instead of writing another 50 blog posts.

What is Clawwork (hkuds)? The Browser Agent That Finally Understands the Web

Yunsoft — Mon, 09 Mar 2026 10:14:19 +0000

I hate Selenium. There, I said it.

I spent last Saturday night debugging a scraper that had been running perfectly for six months. The target website didn't even do a major redesign. They just changed a single CSS class name on their login button. One tiny change, and my entire script exploded.

If you write automation scripts, you know this feeling. It is the absolute worst part of the job. We have been building bots that are "blind" for years. We tell them to click coordinate X or find ID Y. They do exactly what they are told, which is usually the problem.

That is why I stopped scrolling when I saw a repository called hkuds/clawwork popping up all over my GitHub feed recently. It promised to fix the one thing that makes browser automation a nightmare: fragility.

I decided to dig into it because I kept seeing people search for "what is Clawwork" or specifically looking for the hkuds version. I pulled the repo, burned through a bunch of API credits, and gave it a spin.

Here is the honest breakdown of what this thing actually is and if it is worth your time.

Why We Are All Tired of "Dumb" Bots

The problem with tools like Puppeteer or Playwright isn't that they are bad tools. They are amazing. The problem is that they rely on the DOM.

You are basically playing a game of "Where's Waldo" with HTML tags. You write a script that says "Find the blue button." But tomorrow, the button might be green. Or it might be inside a strictly positioned div that blocks the click.

Traditional bots crash when things change. They have no intuition.

Clawwork is different. It is part of this new wave of "Agentic AI." Instead of looking at the code, it uses Large Language Models and computer vision to look at the actual pixels. It sees the page like you do.

So, What is Clawwork (hkuds)?

Okay, let's get technical for a second. Clawwork is an open-source browser automation agent. There are a bunch of versions floating around, but the hkuds/clawwork repo is the one everyone is talking about right now because it is clean and it actually works.

Think of it as a wrapper around Playwright. But instead of you writing the steps, you hook it up to a brain like GPT-4o or Claude 3.5 Sonnet.

You don't write: await page.click('#submit-btn');

You write: "Go to Amazon, search for a mechanical keyboard under $100, and add the one with the best reviews to the cart."

The agent takes a screenshot. It sends that image to the AI. The AI looks at it and says, "Okay, the search bar is at the top. I need to click there."

It is weirdly human. It calculates coordinates based on what it sees, not just what is in the code.

Why the "hkuds" Repo Specifically?

I was wondering this too. Why this specific fork?

It comes down to control. Most "AI Agent" tools right now are expensive SaaS products. You have to pay a monthly fee and you don't really know what they are doing with your data.

The hkuds version is open source. You can clone it. You can run it on your own laptop. You bring your own API keys. It handles the messy stuff like managing the browser context and the vision processing so you don't have to build that from scratch.

I Tried to Break It (And It Kinda Surprised Me)

I didn't want to give it an easy test. I sent it to a travel booking site. You know the kind. Popups everywhere, dynamic date pickers, weird overlays.

My prompt was simple: "Find a non-stop flight from New York to London for next Tuesday."

I watched the browser open on my second monitor.

It sat there for a few seconds. That is the "thinking" phase. Then the mouse moved. It didn't jump instantly like a robot usually does. It slid over to the "One Way" toggle. Clicked it. Then it opened the calendar.,

Clawwork Hkuds Vision Grid Terminal Logs Example

This is the part where my Selenium scripts usually die. The calendar date for "next Tuesday" changes every week. You can't hard code it easily.

Clawwork looked at the calendar, figured out what today's date was, calculated next Tuesday, and clicked the right number. It was slow, sure. But it worked. It felt a little ghostly seeing the mouse move by itself based on visual cues.

Under the Hood

If you are a dev, you probably want to know how the sausage is made. The architecture in the hkuds repo is actually pretty smart.

It has three main layers:

Clawwork architecture diagram driver perception reasoning layer AI workflow

The Driver (The Hands) This is standard Playwright. It handles the actual clicking, typing, and scrolling. Nothing new here.
The Perception (The Eyes) This is the cool part. It captures the viewport state. Early agents tried to turn the HTML into text, which was messy. This version leans on Vision. It overlays a grid or numeric tags on interactive elements. So the AI sees a button labeled "42" and just tells the driver "Click 42."
The Brain ( The Wallet) This is where your API key comes in. The agent sends the state to OpenAI or Anthropic. The model decides what to do next. "I see a popup, I should close it."

The Real Talk: Pros and Cons

I am not going to sell you a dream here. This tech is new and it has some rough edges.

The Good Stuff It heals itself. If the website moves the login button to the left, Clawwork sees it and clicks it anyway. You don't have to update your code. That is huge. It handles logic that is hard to code, like "Choose the best looking option."

The Pain Points It is not cheap. Every single step is an API call with image data. If you are scraping ten thousand pages, you are going to burn through your wallet fast. It is also slow. The "Observe -> Think -> Act" loop takes a few seconds. You are not going to use this for high-frequency trading.

When Should You Use It?

Don't use this to scrape Wikipedia. That is overkill.

Use it for the stuff that makes you want to pull your hair out. Use it for QA testing where you need to simulate a confused user. Use it for complex workflows that involve multi-step forms. Use it for legacy internal tools that have terrible code structures.

Getting It Running

I am not going to lie, the setup can be a bit tricky if you haven't messed with Node or Docker environments before. You need to get your environment variables right or the browser will just close immediately.

I spent a few hours banging my head against the wall getting the Docker container to play nice with my local network.

Clawwork installation guide step by step tutorial setup success terminal

Since I already went through that pain, I wrote a specific guide just for the installation.

Click here to read my full ClawWork Installation Guide

I break down exactly how to configure the .env file and how to avoid the common errors I ran into.

The web is changing. We are moving away from rigid scripts to autonomous agents. hkuds/clawwork is one of the first tools that actually makes this accessible to normal developers. It is messy, it is fun, and honestly, it is probably the future.

Check out the repo, but definitely grab my guide first so you don't waste your evening debugging config files like I did.

Stop Treating Clawdbot (OpenClaw) Like a Plug-and-Play Solution

Yunsoft — Wed, 25 Feb 2026 09:09:17 +0000

Clawdbot (now OpenClaw) isn’t exactly the type of tool that tip-toes into the room. It tends to crash the party all at once. One day it’s a mention in a random thread, the next it’s a blog post link, and suddenly there’s a 30-second “how-to” video making it look like child’s play.

Before anyone actually understands the mechanics, it feels like everyone is already using it. And that’s the problem: expectations usually outpace reality.

From what I’ve seen, Clawdbot sits in a tricky middle ground. It’s powerful enough to be useful, but limited enough to frustrate anyone expecting it to solve problems it was never built for.

What’s Actually Happening Under the Hood?
Strip away the marketing, and at its core, Clawdbot is a scraping bot. It hits a page, reads the structure, and grabs data based on the rules you set. Simple enough on paper, right? In practice, it’s rarely that clean.

The thing is, Clawdbot doesn’t “understand” intent. It doesn’t know which data point is the gold mine and which is just noise. It just follows a pattern. If that pattern shifts even slightly, your output breaks. Period.

A Finished Product or Just a Gear in the Machine?
Most people get disappointed because they treat Clawdbot like a “plug-and-play” solution. Clawdbot shines when it’s treated as one part of a larger ecosystem, not the whole show. It needs to be wrapped in:

Validation layers (is the data actually correct?)

Storage logic (where does it go?)

Monitoring (is the site down or did our logic break?)

Where Expectations Usually Break Down
Scraping projects usually fail for the same boring reasons:

The Stability Myth: Websites are living things. There is no such thing as “set it and forget it.”

The “Garbage In, Garbage Out” Rule: No tool can magically fix a broken data structure without extra logic.

The Scaling Wall: Once you move past small tests, rate limits and error handling start to matter. A lot.

The Bottom Line
Clawdbot starts to make sense the moment you stop looking for a shortcut and start looking at it as infrastructure. If you approach it with a plan and a bit of skepticism, it’s a massive leverage point.

Let's Connect
I share regular notes on automation, data systems, and the reality of implementation here:

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