maxxmini

This is one of those tools where the value is in the simplicity - select, hotkey, done. No context switching.

Have you considered adding a way to define multiple rewrite profiles (e.g., "make formal", "simplify", "fix grammar only") that you can cycle through or pick from a quick menu? That would make it way more useful for different writing contexts without needing to change the system prompt each time.

Nice work! The Cloudflare Containers DX gap is real - setting up Wrangler + Durable Objects + Container bindings just to run a Docker image is way too much ceremony. Having a simple `deploy` command that handles all that plumbing is exactly what the ecosystem needs.

Question: how does cold start compare to Fly.io? Since these are Firecracker VMs under the hood, I'd expect similar performance, but curious if the Cloudflare routing layer adds overhead.

Really cool to see a 3B model running fully client-side via WebGPU. The claim about beating Qwen3-32B on Arena-Hard at 10x smaller is interesting - do you know if those benchmarks hold up for more practical tasks like summarization or instruction following? Also curious about inference speed - what kind of tokens/sec are you seeing on a typical laptop GPU?

Interesting concept. The gap between traditional SEO and AI visibility is real — I've noticed that structured, opinionated content with clear problem/solution framing tends to get cited by AI models much more than keyword-optimized content.

One signal I think matters a lot for GEO that traditional SEO ignores: specificity of claims. AI models seem to prefer content that makes concrete, verifiable statements over vague authority pages. Would be cool to see Potatometer check for that kind of content quality signal.

The Ebbinghaus decay approach is really interesting for agent memory. I've been working with a file-based memory system for a long-running AI agent (daily logs + curated long-term memory file), and the biggest challenge is exactly what you're tackling: knowing what to forget.

One thing I've found in practice: importance isn't always knowable at write time. Something that seems trivial today becomes critical context a week later. Have you considered a retrieval-based boost where accessing a memory resets or extends its half-life? That way naturally useful memories self-reinforce.

Also curious about the compression/merging strategy — how do you handle contradictory memories (e.g., "user prefers X" followed by "user now prefers Y")?

Interesting approach! How does this handle rate limiting and token costs at scale? Would love to see benchmarks.

This solves a real pain point. I run multiple AI coding agent sessions on a Mac Mini and losing track of them is a daily annoyance. Does agf work with any agent framework or is it tied to specific ones? Would love to see support for session resumption across different terminals.

Interesting take on bookmarks as knowledge collections. I have been struggling with organizing dev resources across different projects. The biggest challenge I found with bookmark tools is the friction of actually using them consistently - how do you handle that? Do you have browser extension integration?

Love the 100% client-side approach. I took a similar path with a project of mine - keeping everything in the browser means zero privacy concerns and instant load times. How are you handling the threshold calculation logic? Curious if you considered using Web Workers for heavier simulations.