AI Coding2026
Reviews Git diffs or entire files via a CLI that combines deterministic pipelines (precise file selection, bundling, rule matching) with an LLM agent to produce line-level review comments. Includes built-in security rules and integrations for multiple LLM providers, designed for CI and large changesets.
AI Model2026
A GGUF-format 9B LLM fine-tuned for code generation and agentic tool-calling that uses Multi-Token Prediction (MTP) and draft heads to increase throughput and long-range planning. Intended for local inference and research/experimental coding workflows; Apache‑2.0 license.
MCP Server2026
Provides long-term memory for AI coding agents by compiling sanitized lifecycle observations into a git-versioned Markdown wiki that enables cross-agent handoffs, per-project isolation, and optional vector-backed retrieval.
AI Client2026
Terminal-native AI coding agent that reads and edits code, runs shell commands, searches files, fetches web pages, and determines next steps from interactive feedback. Delivered as a single-binary TUI with video input, subagents, a plugin marketplace, and IDE (ACP) integration.
AI Agent2026
Runs an external, reviewable coding-agent harness that turns intent into repeatable software work: clarifies requirements, builds reviewed plans, executes in tmux-backed sessions, and collects durable verification. Ships Telegram/Discord delivery, a research REPL, and optional desktop-control tools; beta-stage.
AI Client2026
Centralizes indexing and management of local AI coding-agent sessions so you can search, view full context, migrate, resume, and restore conversations across agents and devices. Supports extensible local sources, AI summaries, optional Supabase sync, and Skills management.
AI Agent Papers2026
Measures how coding agents explore repositories by asking them to return a ranked, line-level list of code regions relevant to an issue under a fixed line budget. Covers 848 issues across 203 repos and 10 languages; evaluates coverage, ranking, and context-efficiency to isolate exploration quality.
AI Coding2026
Provides a locally runnable, quantized GGUF release of Gemma 4 12B fine-tuned for Python coding with chain-of-thought distilled from Composer 2.5 and supplemented by Fable 5. Multiple quant options for low‑VRAM setups and execution‑verified training traces. Not safety‑aligned; validate before production.
AI Model2026
A quantized 27B coder LLM fine-tuned for repository-level code generation, multi-turn tool calling, and agentic workflows — packaged for local GGUF/llama.cpp deployment with MTP speculative decoding and trace-inversion SFT. Optimized for developer tooling; experimental and not fully safety-validated.
AI Agent2026
Provides a ruleset and skills that make AI coding agents prefer the simplest correct implementation: reuse existing code, prefer stdlib/native features, and only write minimal new code. Cuts generated LOC, tokens, cost and time while preserving validation and safety.
AI Agent2026
Manages real tmux-backed terminals and AI agents as draggable nodes on an infinite pan/zoom canvas, with a Trello-style kanban view, persistent sessions that survive restarts, mobile companion support, and a browser Server Edition for self-hosting.
AI Model2026
A dense ~9B reasoning LLM optimized for agentic coding and tool-calling that emits explicit chain-of-thought (<think>) blocks and well-formed tool calls. Designed to run on a single 80GB GPU (~19GB bf16), uses self-scaffolding RL and exposes an OpenAI-compatible API.