Heroshot – Define screenshots once, regenerate with one command

Hacker News

I built Heroshot to solve a problem I kept hitting: documentation screenshots go stale and updating them manually is tedious. With Heroshot you define what to capture in a JSON config (URLs, CSS selectors, viewports, light/dark mode), run `npx heroshot`, and get a browser with a visual picker. Click elements to configure captures, close the browser, run `heroshot capture`, and you're done. Features that have been useful in practice: - Visual picker - click elements on a live page instead of writing selectors by hand - Per-domain element hiding - suppress cookie banners, chat widgets globally per domain - Dark/light mode - captures both variants in one run - Annotations - arrows, boxes, highlights baked into the PNG - Native integrations for SvelteKit, Next.js, Nuxt, VitePress - components that serve the right variant (dark/light, viewport) automatically - CI/CD ready - GitHub Actions workflow in one command Two open-source projects adopted it: gander-tools/diff-voyager (replaced a custom Playwright script) and MRI-Lab-Graz/prism-studio (MRI research docs, even mentioned it in their JOSS paper). Happy to answer questions about the design decisions.

Visit product View on Hacker NewsFeb 26, 2026

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

85%85% 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.

TrustMRRLess likely to generate early MRR · Strong signals: widgets · 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 · Missing: plus, platform, intuitive

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

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

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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

Incorrect prediction on native model

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