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Devsyringe – automate injecting dynamic values into static files

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Devsyringe – automate injecting dynamic values into static files

Tired of manually copying tunnel URLs, API tokens, or other dynamic values into config files? Even small tasks like this break flow and are error-prone. I built Devsyringe, a small Go CLI that automates this process. You define rules in a simple YAML file, run a command, and it updates multiple static files automatically. It works for tunnels, API keys, documentation, CI/CD configs — anywhere dynamic values need injecting. I’d love to hear how others handle injecting dynamic values into static files in their workflows. GitHub: https://github.com/alchemmist/devsyringe

Visit productView on Hacker NewsSep 19, 2025
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Product HuntOn track for Day 1 leaderboard · Strong signals: tasks · Missing: mac, agents, macos
83%83% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
46%46% 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
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
41%41% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
29%29% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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