Provides a terminal REPL that gives AI coding agents a persistent, structured context memory (a versionable context tree) which can be synced across machines. Distinguishes itself with local-first TUI workflows, Git-like versioning for knowledge, and broad multi-LLM and agent tool integrations; source-available under Elastic License 2.0.
Browser-based AI development platform that runs tasks inside isolated cloud development environments: natural-language agents read code, run commands, modify files, and integrate results back into Git. Key features include per-task sandboxes, multi-model selection, and an enterprise private-deploy option.
Terminal coding agent forked from Google's Gemini CLI, retuned for Qwen3-Coder with a custom parser and tool protocol. Runs against OpenAI, Anthropic, Gemini, Qwen or local models, and adds subagents, agent teams, auto-memory and MCP.
Teaches agent harness engineering — the permissions, memory, persistence, and coordination layer that lets an LLM act — across 20 progressive lessons, each adding one mechanism with standalone runnable code. Chinese-first, plus English and Japanese.
A template and workflow for feeding AI coding assistants structured context — project rules, code examples, and validation gates — instead of one-off prompts. Centers on Product Requirements Prompts (PRPs) that an agent generates, then executes.
Installs ready-made Claude Code configs — subagents, slash commands, MCP integrations, hooks, and settings — from a catalog of 100+ components via one CLI command. Includes a real-time dashboard to monitor live sessions and token usage.
Spec-driven agentic dev platform that turns a prompt into requirements, a design doc, and sequenced tasks before any code is written, then implements from the spec. Runs across IDE, CLI, web, and mobile; validates output with property-based tests.
Unifies agentic tasks, reasoning, and coding in a single MoE model with 355B total / 32B active parameters and a switchable thinking mode. A lighter 106B-param Air variant trades scale for efficiency; both ship MIT-licensed.
Lets AI coding agents provision and operate a full backend themselves — Postgres with pgvector, OAuth2 auth, S3-style storage, Deno edge functions, and hosting — through one interface, plus an OpenAI-compatible model gateway.
Reviews each pull request for security issues: Claude reads the diff and flags vulnerabilities like injection, auth flaws, and hardcoded secrets as inline comments, with built-in false-positive filtering. Ships as a GitHub Action or slash command.
Adds a lightweight, spec-driven workflow so AI coding assistants agree on requirements before code is produced — creates per-change artifacts (proposal, specs, design, tasks), exposes CLI slash-commands, and integrates with 20+ tools for repeatable AI-driven development.
Chat-driven tool that clones any website and converts it into a working modern React app. Uses a Firecrawl backend to orchestrate multiple LLM providers and offers a fast sandbox preview workflow (Vercel or E2B) for rapid prototyping and iterative edits.