LNB – Cross-platform command manager for binaries and aliases

Hacker News

You build tools. Shell scripts. Docker commands. Things you want to run from anywhere. But every OS has different rules: Mac/Linux: edit .bashrc, .zshrc, mess with PATH, source it Windows: create .bat, set up %PATH%, hope PowerShell respects it You waste time managing commands instead of building things. LNB solves that in one line: npm install -g lnb Then: lnb alias build "docker run -v $(pwd):/workspace node:18 npm run build" build Or: lnb ./my-tool my-tool --help Use cases: Make any binary globally accessible Wrap long dev commands into short aliases Share consistent workflows across your team Example: lnb alias deploy "docker-compose -f prod.yml up -d" lnb alias logs "kubectl logs -f deployment/app" lnb alias test "npm test -- --coverage" Cross-platform: On macOS/Linux → symlinks or shell scripts in /usr/local/bin On Windows → .cmd wrappers in %USERPROFILE%\bin Works in Bash, Zsh, CMD, PowerShell, Windows Start menu search Built for: Developers who build CLIs or run local scripts Teams who want consistent dev commands across machines Anyone tired of tweaking PATH manually Links: GitHub: https://github.com/muthuishere/lnb NPM: https://www.npmjs.com/package/lnb

Visit product View on Hacker NewsAug 30, 2025

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2points

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

84%84% 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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% 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 · Missing: mobile apps, ios, personal

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

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

33%33% 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

14%14% 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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