Pincher is a reflex engine — it sits between an agent's intent and the world, intercepting patterns before they reach expensive machinery. quilt-pincher is a from-the-ground-up Quilt-synergistic version where every layer of the engine is a Quilt cell: the pinch is a formula cell, the match is a program cell, the store is a vector_store cell, the veto is a listener cell, the LLM compiler is an ai cell.
Browser, Node, Cloudflare Workers. Full features: real embedders, LLM compiler, federated storage, R2 mirror.
💻 Workstation
Node + SQLite + sqlite-vec. Persistent reflexes that survive restarts.
🔌 ESP32
no_std Rust. Subset: in-memory, no LLM, reflexes loaded from pre-compiled .nail bundle.
Pinch something —
list running containersshow me containerswhat's running on the hostcheck disk spacehow much disk freeshow memory usagedeploy the servicerestart the apiview logs
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fast
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medium
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slow
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reflexes
Reflex database
No reflexes yet. Pinch something new to compile one.
Execution log
Pinches will appear here. Fast = direct hit, no LLM. Medium = confirm + execute. Slow = LLM compile new reflex.
How it works: each pinch embeds the trigger into a 384-dimensional vector, queries the in-memory store for top-K reflexes, and dispatches to the appropriate tier. Fast tier (<50ms): direct hit, no LLM, no thinking. Medium tier (~1s): confirm + execute, slight overhead from confirmation. Slow tier (~5s): LLM compiles a brand-new reflex, which is then stored for next time. The whole engine is a Quilt sheet — the same code runs on cloud, workstation, and ESP32. View the source on github.com/SuperInstance/quilt-pincher.