Op

Open-source, privacy-focused developer tools (early stages)

Hacker News

Open-source, privacy-focused developer tools (early stages)

Hi HN! Many developers use websites to handle menial everyday tasks like formatting json, generating uuid's, etc. The problem that we found with this is that many of these websites send our data to the server to process it. This didn't sit very well with us, considering it could contain customer's information, so we decided to build these tools internally and open source them. For most cases, this processing can be done on the client side without any need for the data to leave your browser. In the spirit of being privacy-focused, we don't track usage levels of this and we certainly don't send any data to a backend service. As I mentioned in the title, this project is in the early stages at the moment but we wanted to share it to get feedback and see if people find it useful. If you do have feedback, let me know in the comments here or feel free to add an issue to the GitHub repository: https://github.com/DevScreenInternal/ds-devtools .

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2points
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Product HuntOn track for Day 1 leaderboard · Strong signals: tasks, open · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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