This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Contribute to egn-labs-dev/ContextSniper development by creating an account on GitStop dumping your entire codebase into Claude or ChatGPT. ContextSniper is a 100% local CLI tool that uses the BM25 algorithm and dependency graphs to extract ONLY the relevant files for your prompt. If the code exceeds your token budget, it automatically strips files down to class and method signatures. Save money, reduce API bills, and fix the "Lost in the Middle" effect in under 250ms.Hub.
Hey ProductHunt community! 👋
As a developer working with LLMs daily, I noticed a huge issue: dumping an entire repository into Claude or ChatGPT Canvas ruins the model's accuracy due to the 'Lost in the Middle' effect, and it completely drains your token budget.
Standard tools act like dumpsters — they just pack everything. I wanted a scalpel. That’s why I built ContextSniper. It runs 100% locally, parses your import chains to build a dependency graph, and uses BM25 scoring to extract only the files needed for your specific task (e.g., npx context-sniper "fix auth middleware").
If the code exceeds your budget, it automatically strips files down to class/method signatures so you never overflow your limits. It's fully open-source and ready to run via npm. Would love to hear your feedback!
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About ContextSniper on Product Hunt
“Smart task-driven LLM context optimizer”
ContextSniper was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #16 on the daily leaderboard. Contribute to egn-labs-dev/ContextSniper development by creating an account on GitStop dumping your entire codebase into Claude or ChatGPT. ContextSniper is a 100% local CLI tool that uses the BM25 algorithm and dependency graphs to extract ONLY the relevant files for your prompt. If the code exceeds your token budget, it automatically strips files down to class and method signatures. Save money, reduce API bills, and fix the "Lost in the Middle" effect in under 250ms.Hub.
ContextSniper was featured in Open Source (68.5k followers), Developer Tools (514k followers), Artificial Intelligence (471k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 207.8k products, making this a competitive space to launch in.
Who hunted ContextSniper?
ContextSniper was hunted by EGN Labs. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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EGN Labs