Infinite SCP Generator

Hacker News

I work at .txt, the Outlines maintainers, and did this as a fun side project. I used Outlines to structure language model output in the format of an SCP entry. SCP entries have a specific structure. It's easy to get a language model to generate these structures via JSON without fail -- no parsing errors, no trailing commas, no missing brackets. Outlines ensures that all text generated will follow the SCP structure. We're also testing an internal structured text API, and figured this might be a good way to test out repeated, regular calls. Entries are generated at midnight and uploaded to a simple website. Check out the resulting entries here: https://dottxt-ai.github.io/cursed/scp/entries/

Visit product View on Hacker NewsOct 24, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

68%68% 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.

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

62%62% predicted probability of success on Product Hunt, 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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive

38%38% 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

20%20% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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