BashForm – Create and fill forms in your terminal via SSH

Hacker News

Instead of boring web forms, create and share forms right in your terminal using SSH. No browsers, no apps, just pure terminal goodness. Key features: - Instant form sharing using simple codes (ssh -t bashform.me f yourcode) - Authentication via SSH keys - Create forms with rich inputs (text, textarea, select) - View responses in the terminal - Zero installation for users - if you have SSH, you're ready - Beautiful TUI (this is subjective xD) Try it instantly: ssh -t bashform.me f try Built with Go and Charm libraries for a snappy, modern terminal experience. P.S. BashForm is actively being developed with new features added regularly. Star the repo to follow the journey and feel free to suggest features! Repo: https://github.com/devmegablaster/bashform

Visit product View on Hacker NewsDec 27, 2024

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

81%81% 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 · Missing: supports, reddit linkedin, podcasting

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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