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Headroom: a live gauge of your AI chat's remaining context, so you know before the AI starts forgetting. Free & open source. Built after DeepSeek started contradicting decisions settled 20 rounds earlier — no platform shows remaining context. Tokens from a 6-writing-system model calibrated against real tokenizers. Text is read, counted, discarded — no server, no API keys. ChatGPT · Gemini · DeepSeek · Kimi · Qwen · Qianwen · Doubao · github.com/ZM-BAD/headroom
Hey PH! I built Headroom after a long DeepSeek session started contradicting decisions we'd settled 20 rounds earlier — the context window had silently overflowed and nobody had told me. None of the major AI chat platforms show remaining context in the UI, so I made a gauge.
A few things I'd love feedback on:
1. It estimates tokens with a linear model over 6 writing systems, calibrated against each platform's actual tokenizer (tiktoken o200k_base, DeepSeek's BPE, Qwen's BBPE...). ±15% on natural language, with known error modes on code-heavy and mixed-script text. Is there a better lightweight approach that fits in a ~70 KB extension? WASM tokenizers were too heavy.
2. The MV3 sidePanel + action.disable() bug — Chrome officially says "Works As Intended", so the workaround is a 3-D per-tab ACL (icon swap + onClicked + setOptions). Any sidePanel devs hit the same wall?
3. Which AI platform should I support next?
It's free, no signup, no API key — install from the Chrome Web Store / Edge / Firefox (links in the README). Happy to answer questions all day.
The fact that it runs locally without API keys and never stores your text is a really thoughtful design choice, especially for something meant to monitor sensitive chat sessions.
About Headroom on Product Hunt
“A live gauge of your AI chat's remaining context”
Headroom was submitted on Product Hunt and earned 2 upvotes and 2 comments, placing #157 on the daily leaderboard. Headroom: a live gauge of your AI chat's remaining context, so you know before the AI starts forgetting. Free & open source. Built after DeepSeek started contradicting decisions settled 20 rounds earlier — no platform shows remaining context. Tokens from a 6-writing-system model calibrated against real tokenizers. Text is read, counted, discarded — no server, no API keys. ChatGPT · Gemini · DeepSeek · Kimi · Qwen · Qianwen · Doubao · github.com/ZM-BAD/headroom
Headroom was featured in Chrome Extensions (52.7k followers), User Experience (367.4k followers), Artificial Intelligence (475.6k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 185.8k products, making this a competitive space to launch in.
Who hunted Headroom?
Headroom was hunted by 周铭. 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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