Repeat file reads and commands come back in under a millisecond — and stop bloating your agent's context.
✓ installed— zero dependencies, pure Python stdlib
02/ the problem
The Context Snowball
LLM context accumulates everything. Every file read and command output stays in context forever — even exact duplicates.
session context0 tokens
Red blocks are repeat reads of the same file. You pay for them linearly — and the GPU pays O(N²) attention on every turn. That's a latency tax on your time.
03/ how it works
Miss once. Hit forever.
ToolRecall sits between your agent and the OS. First call executes live and is cached — every identical call after skips the OS entirely.
04/ context tracker
Breaking O(N²) growth
The tracker knows which files the agent wrote (dirty) vs. only read (clean). Clean content is dropped from context — and re-served from cache in ~0.6ms if needed.