Indexes any codebase into a knowledge graph — dependencies, call chains, clusters and execution flows precomputed — then serves it to coding agents through 17 smart MCP tools so Cursor, Claude Code and Codex never miss code.
A single Rust binary that runs coding agents as always-on background terminals: panes report working, blocked or idle, agents drive each other through a CLI and socket API, and sessions survive restarts.
Genesis AI's open simulation platform for physical AI: one Pythonic API over a multi-physics engine (rigid, FEM, MPM, PBD, SPH, Stable Fluid, IPC), the Nyx path tracer, and Quadrants, a cross-platform Python-to-GPU compiler. It is built to be the evaluation engine for robot foundation models rather than a data factory: 30,000 parallel environments at 43M FPS, and under a zero-shot real-to-sim protocol, sim-vs-real evaluation agreement of Pearson 0.8996 with mean maximum rank violation 0.0166. Apache 2.0, 29.9k stars.
An agent skill for Claude Code, Codex and OpenCode that rebuilds a reference image as a code-only procedural Three.js model: an eight-pass sculpting pipeline with deterministic gates, shipping a diffable TypeScript factory instead of a mesh.
AO is a local desktop workspace: each coding task gets its own agent, isolated worktree branch and feedback loop; a project-aware orchestrator shapes plans and spawns workers; a live Kanban tracks every PR, CI run and review. Supports 26 coding agents.
LoopX is an open, provider-neutral, stateful control plane that runs on top of Codex, Claude Code, Cursor and other agent harnesses instead of replacing them. It preserves objectives, gates, todos, scope, evidence, quota and handoffs as durable state across turns, restarts and agents, and uses quota to decide whether a loop may continue, keeping multi-day work reviewable, restartable and handoff-able.
OpenResearch (orx) is alphaXiv's local-first research workspace: a single Rust binary that turns Claude Code, Codex, OpenCode, or Cursor into research agents that review literature, form hypotheses, run experiments, and produce artifacts. It organizes work as a git-native experiment tree under a fixed run contract, drives experiments through a repair/refill/promote/stop autoresearch loop, and treats run logs and manifests as the only evidence. Written from a close read of the v0.2.3 source and a hands-on run of the bundled nanochat demo.
A from-scratch C++/CUDA inference engine for five explicitly registered Qwen checkpoints on one NVIDIA GeForce RTX 5090. Startup-frozen residency picks MTP or DFlash speculative decoding, Vision, and one of five KV storage formats; a shared Device KV pool plus pinned Host State/KV checkpoints reuse exact prompt prefixes across 240k-token contexts. Measured aggregate decode reaches 1,146.9 tok/s at concurrency 8 and 15,544.3 tok/s on a 7,680-token prefill.
A one-stop VLA toolbox from Dexmal: the unified DexData format spans pretraining, fine-tuning (full/LoRA/RL), inference, and evaluation, supporting mainstream models (π0, CogACT, OFT, MemVLA, GR00T N1) plus the in-house dual-expert DM0; DB-pretraining brings consistent gains across five simulation benchmarks, with 62% average success on RoboChallenge Table30 real-robot evaluation.
A fixed-protocol harness for comparing image-to-3D models. One set of AI renders of a fictional submersible goes into TRELLIS V1/V2 and TripoSR; each mesh is inspected through an identical Blender 4.3 EEVEE orbit and scored on a 0-2 five-axis rubric, then the winner ships into a Three.js + three-mesh-bvh explorer with real collision. TRELLIS V2 stochastic ranks first at 1.56 MB / 11,866 faces.
Bimo is a 45 cm, roughly 1.6 kg hip-head biped kit: eight STS-3215 bus servos, a BNO08x 9-DoF IMU, four VL53L0X rangefinders, two 180-degree cameras, and a custom RP2040 board closing a 20 Hz control loop. The repository publishes the Python control API (1023 lines), three MCU firmware builds (1349 lines), a ROS2 wrapper (1431 lines) and an Isaac Lab training environment (874 lines: six reward terms, dense domain randomization, and a system-identified STS3215Actuator with 3.113 Hz bandwidth, directional gear backlash and a 5 ms bus delay), plus a 26MB Bimo.usd model. The CPG gait's 104 Fourier coefficients and per-joint amplitude gains are hardcoded in both Python and C, and a [256,128,64] PPO teacher distills into a [64,32] student that goes through onnx2c into the firmware, so the robot walks untethered on the MCU. All code is Apache-2.0, but the CAD and electronics the README promises are still marked coming soon: no STL, STEP, schematic, gerbers or BOM exist in the working tree or in git history, and neither release ships pretrained weights (zero assets) or a DIY assembly manual. Currently v1.1.0 with 198 stars, in pre-order status.
Open-source causal world model from Seedleap.ai: text prompts and keyboard actions alter world evolution in real time. Causal KV cache + four-step DMD sampling enable long-horizon real-time rollouts on a single GPU; No.1 real-time world model on WBench.