Selfcommit.dev VS Algolens.trade

Compare Selfcommit.dev VS Algolens.trade and see what are their differences

Rating: 0 reviews

Rating: 0 reviews
Pricing: Paid €49 / Monthly (1 license that can be use in several computers at a time)

mbuzz.co

Multi-touch attribution that shows the model behind the number. 8 models compared side-by-side, a SQL-like DSL to write your own, and open-source SDKs for Ruby, Node, Python, and PHP. Runs server-side. Your data, not theirs. sponsored

Base details

Website, pricing, platforms and company facts side by side.

	Selfcommit.dev	Algolens.trade
Website	selfcommit.dev	algolens.trade
Pricing	—	Paid €49 / Monthly (1 license that can be use in several computers at a time) Official pricing
Platforms	—	Windows
Listed in	—	Trading Mql5.com MQL Marketing Analytics Web Analytics Data Analysis Analytics No Code Windows Tools +6

Analysis

An editorial look at what each product does well and who it suits.

Selfcommit.dev

Algolens.trade

Overall verdict

Selfcommit.dev appears to be a niche accountability/goal-tracking tool aimed at helping individuals commit to personal or professional goals, but there is limited widespread public information, reviews, or track record available to fully verify its quality, reliability, or long-term support.

Why this product is good

Focuses on personal accountability through structured commitment tracking, which can be motivating for self-improvement
Likely has a simple, developer-friendly interface given the '.dev' domain branding
May offer a lightweight, distraction-free alternative to bloated habit-tracking apps
Could be a good fit for solo builders or indie hackers who prefer minimalist tools

Recommended for

Individuals looking for a simple self-accountability or commitment-tracking tool
Developers or indie hackers who prefer niche, no-frills apps over mainstream productivity suites
Users comfortable trying newer, less established platforms
People who want lightweight goal or habit tracking without complex features

No analysis of Algolens.trade yet.

Questions & Answers

As answered by people managing Selfcommit.dev and Algolens.trade.

Which are the primary technologies used for building your product?

Algolens.trade's answer:

It's a Windows desktop app. The interface is plain HTML and JavaScript. There's no cloud service in the middle, everything runs on your own machine, so your research stays local.

What makes your product unique?

Algolens.trade's answer:

The MQL5 Market only lets you look at one product page at a time. AlgoLens pulls the whole public catalogue into a single table you can actually filter and sort. So instead of clicking through hundreds of listings, you sort every Expert Advisor and indicator by price, rating and how recently people reviewed it, and you see at a glance which ones have real demand. It also splits buy vs rent pricing and shows what the seller keeps after the Market's 20% cut, which normally you'd have to work out by hand.

Why should a person choose your product over its competitors?

Algolens.trade's answer:

Honestly there isn't a direct competitor that does this. People either browse the MQL5 Market by hand, or they copy numbers off listings into a spreadsheet that goes stale the moment they stop updating it. AlgoLens does that work for you and keeps it in one place. Compared to a generic scraping tool, this one is built specifically around the MQL5 Market and its quirks (the commission, the rating and review data, MT4 vs MT5), so the columns and filters are the ones you'd actually want.

How would you describe the primary audience of your product?

Algolens.trade's answer:

People who build or sell Expert Advisors and indicators on the MQL5 Market. Mostly independent developers and small software sellers who want to research pricing, demand and what the competition is doing before they list a product or set a price. It's a research tool for the sell side, not for traders looking for signals.

What's the story behind your product?

Algolens.trade's answer:

I kept wanting to know which products on the MQL5 Market were actually selling, and at what price, and there was no good way to see it. The site shows one listing at a time with no way to sort by demand, so I ended up copying numbers into spreadsheets over and over. Eventually I built a small tool to do it automatically, then kept adding filters and columns until it was more useful than the spreadsheet. That's what became AlgoLens.

User comments

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