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VIC-E TokenSaver
Local, cross-client token savings with built-in evidence
TokenSaver is a local context optimizer for Claude Code, Codex, Gemini, Grok, and other AI coding tools. It reduces repetitive logs, searches, file reads, and tool output before they consume paid model context. Unlike command-specific reducers, it provides one cross-client proxy, a native Rust engine, fail-open processing, adjustable profiles, and evidence reports showing measured savings, overhead, failures, and per-client results. Windows, macOS, and Linux; free for personal home use.
Hi Product Hunt! We built TokenSaver after seeing AI coding agents repeatedly fill their context with long logs, searches, file reads, and test output instead of the information needed to finish the task.
Context reduction already exists in tools such as RTK and Headroom, as well as built-in client compaction. TokenSaver is different in its combination of one cross-client local proxy, a native Rust engine, bounded fail-open processing, adjustable profiles, and evidence generated from your own workflow.
Instead of showing only a savings percentage, TokenSaver reports measured tokens before and after optimization, local processing overhead, failures, and per-client results. You can connect Claude Code, Codex, Gemini, Grok, or another supported client, work normally, and generate a self-contained QA report to judge the tradeoff yourself.
In our published 32-scenario benchmark, VIC-E reduced 282,323 benchmark tokens to 60,917 while passing all 32 fidelity checks. We publish the methodology and limitations because this is maintainer-run evidence and should be open to scrutiny.
TokenSaver runs on Windows, macOS, and Linux. Personal, non-commercial home use is free.
I’d especially value difficult feedback: output that should remain exact, missing context, integration problems, or workloads where the overhead is not worthwhile. Thanks for trying it, I’ll be here answering questions throughout the launch.
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About VIC-E TokenSaver on Product Hunt
“Local, cross-client token savings with built-in evidence”
VIC-E TokenSaver was submitted on Product Hunt and earned 1 upvotes and 1 comments, placing #160 on the daily leaderboard. TokenSaver is a local context optimizer for Claude Code, Codex, Gemini, Grok, and other AI coding tools. It reduces repetitive logs, searches, file reads, and tool output before they consume paid model context. Unlike command-specific reducers, it provides one cross-client proxy, a native Rust engine, fail-open processing, adjustable profiles, and evidence reports showing measured savings, overhead, failures, and per-client results. Windows, macOS, and Linux; free for personal home use.
VIC-E TokenSaver was featured in Productivity (660.2k followers), Developer Tools (519k followers) and Artificial Intelligence (478.1k followers) on Product Hunt. Together, these topics include over 361.4k products, making this a competitive space to launch in.
Who hunted VIC-E TokenSaver?
VIC-E TokenSaver was hunted by VIC-E. 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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VIC-E
Hi Product Hunt! We built TokenSaver after seeing AI coding agents repeatedly fill their context with long logs, searches, file reads, and test output instead of the information needed to finish the task.
Context reduction already exists in tools such as RTK and Headroom, as well as built-in client compaction. TokenSaver is different in its combination of one cross-client local proxy, a native Rust engine, bounded fail-open processing, adjustable profiles, and evidence generated from your own workflow.
Instead of showing only a savings percentage, TokenSaver reports measured tokens before and after optimization, local processing overhead, failures, and per-client results. You can connect Claude Code, Codex, Gemini, Grok, or another supported client, work normally, and generate a self-contained QA report to judge the tradeoff yourself.
In our published 32-scenario benchmark, VIC-E reduced 282,323 benchmark tokens to 60,917 while passing all 32 fidelity checks. We publish the methodology and limitations because this is maintainer-run evidence and should be open to scrutiny.
TokenSaver runs on Windows, macOS, and Linux. Personal, non-commercial home use is free.
I’d especially value difficult feedback: output that should remain exact, missing context, integration problems, or workloads where the overhead is not worthwhile. Thanks for trying it, I’ll be here answering questions throughout the launch.
Nick.