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signet – code signing tool

Hacker News

signet – code signing tool

Hello HN, I've built signet, a code signing tool that makes it really easy to sign your git commits and arbitrary files such as build outputs. signet uses OpenSSH's key and signature formats, making it easy to migrate from, or to, ssh-keygen or another compatible tool. signet runs on Linux, macOS, and Windows. The following commands will create a new signing key and configure git to sign all future commits and tags in the current repository: signet init -s signet keys -c git config user.signingkey <key id> git config gpg.format ssh git config gpg.ssh.program signet git config commit.gpgsign true git config tag.gpgsign true GitHub supports commit signature verification for SSH signatures, just print the public key with `signet keys -p <key id>` and add it to your account, and your signed commits and tags will show up as verified.

Visit product View on Hacker NewsJan 10, 2023

Actual performance

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Launch Intel predictions

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

78%78% 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: supports, compatible · Missing: reddit linkedin, podcasting, created

64%64% 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

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

18%18% 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.

Incorrect prediction on native model

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