RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows,...
Orchestrates a triple-AI engineering loop where Claude plans, Codex validates logic and reviews code, and Cursor implements, with continuous feedback for optimal code quality
Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+...
Help users run effective one-on-one meetings. Use when someone is a new manager setting up 1:1s, struggling to make 1:1s productive, wants to improve career conversations with reports, or needs to...
Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster...
Train Mixture of Experts (MoE) models using DeepSpeed or HuggingFace. Use when training large-scale models with limited compute (5× cost reduction vs dense models), implementing sparse...
Delegate tasks to Codex CLI to save Claude context
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Professional code review with auto CHANGELOG generation, integrated with Codex AI
Run the Codex Readiness unit test report. Use when you need deterministic checks plus in-session LLM evals for AGENTS.md/PLANS.md.
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support
Intelligently delegate code generation, boilerplate creation, and automation tasks to OpenAI Codex CLI for rapid prototyping and development.
Run the Codex Readiness integration test. Use when you need an end-to-end agentic loop with build/test scoring.
test-skill-1 skill
Summarize huge articles (URL or local file) via a Codex CLI-driven chunk→reduce pipeline, keeping only the final short summary in context and saving it to summaries/*.md.
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive...