CredWork – a simple project tracking and showcasing tool

Hacker News

Hi HN, I'm Tushar, founder of CredWork - a simple project tracking and showcasing tool to use manually or with your AI Agent. It started as a simple timeline tool and then I added a way to collect projects to show in a portfolio website. You can try it for free without signing up. If you create an account, it creates a track record of your activity, similar to the Github heatmap. Once you have enough activity, it calculates badges for consistency and AI skills (more coming). I personally use it a lot through the mcp server so I can have my coding agent create and update tasks as it's working. It then becomes the conversation context that I can reuse in another conversation, across products. I would love to get some feedback and suggestions.

Visit product View on Hacker NewsMay 26, 2026

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Actual performance

3points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, mcp, context · Missing: mac, agents, macos

88%88% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

42%42% 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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% 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.

Correct prediction on native model

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