Overflow – compact your context window before it overflows
One tagline and a screenshot with no working demo or docs.

Another context management pitch when Cursor and Continue already solve this.
Developers building long-horizon AI coding agents
Cursor · Continue · Cline
This blog post walks through our approach to long-horizon agents, long-context LLMs, harness-driven context management, and our model-driven context state compression.
Try GLM-5.2 hosted by Subconscious.dev using the examples in the post. The model keeps running until the message list outgrows your internet connection where your WiFi becomes the bottleneck before context window.
One tagline and a screenshot with no working demo or docs.
SLM classifiers compress context based on tool call intent before LLM sees it.
Persistent memory for Claude Code with auto-compaction recovery—but relies entirely on external API.
Entropy-based context compression beats naive token stuffing, but the category is crowded.
Tree-sitter AST compression cuts LLM context tokens 50-70% while preserving API structure.
Smart hysteresis compaction for Claude Code, but limited to single API and not a general problem.