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TokenCount Context Bundler
Save 90% AI tokens via Semantic Dehydration & .cursorrules
Stop paying for wasted tokens. ContextBundler "dehydrates" your entire repo into logic-aware AI context. It prunes JSDoc, logs, and boilerplate while keeping logic 100% readable for Cursor and Claude. Features built-incursorrules generation.
A few weeks ago, my Cursor/Claude bill hit triple digits. I realized 80% of what I was feeding the AI was just "token garbage"—massive JSDocs, redundant logs, and empty lines that the AI didn't actually need to "see" the logic.
So I built ContextBundler (and the TokenCount matrix).
Unlike simple file-mergers, it uses a Semantic Skimming algorithm. It prunes the implementation fluff but keeps the "logic map" intact, slashing token usage by up to 90% without breaking the AI's understanding.
What’s in the Matrix? ✅ CLI: npx @xdongzi/ai-context-bundler@latest . ✅ VSCode: Lives in your sidebar for instant skimming. ✅ Chrome: Grab clean Markdown from heavy docs (like react.dev).
🎁 LAUNCH GIFT: I’ve unlocked all Pro features for 50%OFF today to celebrate our launch!
I'd love to get your feedback: What’s the messiest repo you’ve tried to feed into an LLM? Let me know in the comments! 🛡️
About TokenCount Context Bundler on Product Hunt
“Save 90% AI tokens via Semantic Dehydration & .cursorrules”
TokenCount Context Bundler was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #41 on the daily leaderboard. Stop paying for wasted tokens. ContextBundler "dehydrates" your entire repo into logic-aware AI context. It prunes JSDoc, logs, and boilerplate while keeping logic 100% readable for Cursor and Claude. Features built-incursorrules generation.
On the analytics side, TokenCount Context Bundler competes within Developer Tools and Artificial Intelligence — topics that collectively have 979k followers on Product Hunt. The dashboard above tracks how TokenCount Context Bundler performed against the three products that launched closest to it on the same day.
Who hunted TokenCount Context Bundler?
TokenCount Context Bundler was hunted by JustinX. 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.
For a complete overview of TokenCount Context Bundler including community comment highlights and product details, visit the product overview.
JustinX
Hey Product Hunt! 👋 I’m Justin, the maker behind JustinXai Labs.
A few weeks ago, my Cursor/Claude bill hit triple digits. I realized 80% of what I was feeding the AI was just "token garbage"—massive JSDocs, redundant logs, and empty lines that the AI didn't actually need to "see" the logic.
So I built ContextBundler (and the TokenCount matrix).
Unlike simple file-mergers, it uses a Semantic Skimming algorithm. It prunes the implementation fluff but keeps the "logic map" intact, slashing token usage by up to 90% without breaking the AI's understanding.
What’s in the Matrix?
✅ CLI: npx @xdongzi/ai-context-bundler@latest .
✅ VSCode: Lives in your sidebar for instant skimming.
✅ Chrome: Grab clean Markdown from heavy docs (like react.dev).
🎁 LAUNCH GIFT: I’ve unlocked all Pro features for 50%OFF today to celebrate our launch!
I'd love to get your feedback: What’s the messiest repo you’ve tried to feed into an LLM? Let me know in the comments! 🛡️