Skill Claude CodeCodex
Compress images, long prompts, conversations, and RAG documents locally via Ollama before consuming LLM tokens. Reduces token usage by 80% on images and 85% on text. Use proactively when: the user uploads images, processes long context, works with multiple RAG sources, or when approaching token limits.
Cursor rule Cursor
Add this file to your project root as .cursorrules to make Cursor automatically use LatentGate for token compression.
Plugin Claude Code
Bundles 1 skill, 1 MCP server · 88 tokens together
Token optimizer for Claude: read large logs, JSON/API dumps and documents in a fraction of the context. Deterministic, fact-preserving, offline.
MCP server Claude CodeCodexCursor +2
Local-first vision-language pipeline inspired by VL-JEPA. Compress images, text, conversations, and RAG documents locally via Ollama before sending to any LLM API. Deterministic, fact-preserving token optimizer plus MCP server, FastAPI server and video processing. Runs locally from the latent-gate Python package.