Forgecode

ForgeCode's pitch is narrow and it delivers on it: an AI coding agent that never leaves your shell prompt. The ZSH plugin is the whole interface — you type ':' and a space, then a prompt in plain English. That matters more than it sounds. Most terminal AI tools ask you to context-switch into a separate TUI, a browser tab, or an IDE panel; ForgeCode keeps your aliases, your Oh My Zsh plugins and your cwd exactly where they were. The benchmark story is unusually well-documented for this category. ForgeCode went from 78.4% on TermBench 2.0 with Gemini 3.1 Pro to 81.8% with GPT-5.4 and Opus 4.6, and the team published the seven failure modes that got them there. Compare that to the static homepage copy, which still leans on the older number. In the same eval set, Claude Code sits at 58% and Warp at 61.2%. Treat benchmark scores as directional — your repo is not TermBench — but the harness was clearly built to be measured. The model flexibility is where ForgeCode separates from single-vendor tools. You can run a thinking model to plan, swap to a fast model to write the diff, and pull in a large-context model for a big file, without restarting the session. OpenRouter covers 300+ models on one key, and the docs explicitly support open-weight models (GLM, Kimi, Minimax) and locally hosted models, not just the frontier APIs. The multi-agent split across Forge, Muse and Sage is the mechanism that keeps this coherent: each sub-agent runs on bounded, task-relevant context rather than one giant window, which is what makes long multi-step runs reliable enough to trust on real work. ForgeCode Services is the layer most people underestimate. The context engine, semantic search across a large codebase, and tool-call corrections aimed at keeping local models on track are exactly the failure points that make open-weight models frustrating to use for agentic coding. It works without an API key. If you're running a 32B local model and it keeps fumbling function calls, this is the feature that decides whether the setup is usable. What it is not: a managed service. You install the binary, run a setup wizard, log into a provider, pick a model, and restart your terminal before the ':' trigger works at all. The docs call that restart out as the most common cause of a broken install, and there's a 'forge zsh doctor' command for when it still misbehaves. Not every terminal or shell setup will be friction-free, and Windows users are routed through WSL or Git Bash rather than a native build. There is also a VS Code extension documented, but the product's center of gravity is unambiguously the shell. Best fit: terminal power users on large codebases, teams benchmarking coding models, and developers who already pay for multiple providers and want to route each task to the right one. Poor fit: IDE-first developers, anyone who will not touch a Zsh config, and teams that want a vendor to handle model access for them.