Jobsearch – unified CLI for scraping job boards

Hacker News

Author here. Got tired of checking Upwork, NoFluffJobs, eFinancialCareers, LinkedIn and HN threads separately, so I built a CLI that scrapes them into a local SQLite DB and lets me browse everything in one web UI with filters and semantic search. Details: - Scraping via real browser over CDP (your own logged-in session, no API keys) - Embeddings run locally (nomic-embed-text via fastembed), stored in Lance - Rust backend, SolidJS frontend embedded in binary, single static executable Works for my use case (Europe-based contractor). It's my first rust project, decided to do local CLI, it's helpful for me (more providers will be added, feel free to contribute).

Visit product View on Hacker NewsJul 29, 2026

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Actual performance

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Did not reach leaderboard

Launch Intel predictions

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

80%80% 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.

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

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: para · 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 · Missing: arr, mrr, revenue

22%22% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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