Ki

KissTodo – Focused and Effective Prioritization

Hacker News

KissTodo – Focused and Effective Prioritization

Yeah yeah, another todo app . But not really. KissTodo spawned from my dislike of the currently available task management tools. It combines focus and simplicity to offer an improved experience over the other solutions on the market. Most developers try to create a todo app as their first app and as such does not come from a real need and provides no real value. I was truly disenchanted with the current task management apps out there and I am truly satisfied with KissTodo (been using it for close to 6 months). I don't know if KissTodo is for you or not, but I believe it can bring value to those that like flexibility, simplicity, minimalism and nimbleness. That being said, I'm ready to get roasted I welcome any comment, discussion, suggestion or insult haha Cheers!! (My apologies for reposting, I really wanted to do a proper "Show HN" and also post with a working link )

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1points
4comments
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRLess likely to generate early MRR · Strong signals: apps, month · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Strong signals: apps, using · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
25%25% 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
12%12% 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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