F1 Replay Timing

HFTENGINE is a replay console and backtesting application for market-making strategies using the hftbacktest crate. It runs tutorial strategies against recorded Binance USDT-M Futures order-book and trade data, replaying the local order book, resting orders and estimated queue positions, feed and order latency, market trades, executions, raw collector feed, and runner statistics frame by frame. Its Rust runner records the replay and its Vite/TypeScript dashboard presents the session in a text-mode interface. The project models post-only limit-order fills with hftbacktest's queue and exchange models; queue position is estimated from level-2 data, and order latency is derived from recorded feed latency rather than measured live. It includes tools to collect public Binance websocket data, convert recordings into sessions, run the backtest, and inspect replay moments. HFTENGINE is explicitly a backtester and replay screen: it does not place orders, compute or display P&L, or configure live trading.

fx0 is an open-source web application and lightweight design agent from Vercel Labs, built with libfx. A user describes a page and the agent produces it as a single HTML file, with a live sandboxed preview, design editing and publishing tools, web search and page-fetching tools, and optional subagents. The app stores chats and design versions, allowing previous versions to be reopened or downloaded. libfx supplies the agent loop, streaming, tool calls, retries and durable sessions; on Vercel, Vercel World and Vercel Queues let a turn continue after the function handling it crashes or reaches its time limit. Model calls are billed through Vercel AI Gateway using the signed-in user's team, with an optional sponsored trial. The repository includes local setup and deployment instructions using Node.js, Neon Postgres and Upstash Redis. It is licensed under Apache-2.0; its bundled design styles come from VoltAgent's awesome-design-md under the MIT license.

tapflow is a self-hosted mobile QA platform for streaming iOS simulators and Android emulators to a team’s browser. It uses a relay server, a macOS agent that drives the simulators and emulator, and a browser dashboard connected through WebSockets; the agent connects outbound to the relay and does not require WebDriverAgent. QA users can interact with devices in real time without installing Xcode, Android Studio, or local simulator tooling. The platform supports build uploads, status tracking, touch and gesture input, clipboard synchronization, device audio, network control, deeplinks, session recordings, team roles, REST endpoints, and personal access tokens. It also includes an experimental YAML flow runner that produces JUnit reports and an experimental MCP server for controlling simulators through LLM agents. The relay can run on Linux or macOS, while agents run on macOS, and the project is distributed under the MIT license.

Fast Browser Use is a local-first browser automation engine and agent skill for Claude Code, Codex, Cursor, and Python workflows. It runs Qwen3.5 models locally through MLX or PyTorch on Apple Silicon, CUDA GPUs, or CPUs, without cloud inference. The engine scans the rendered page for visible, interactable controls and converts them into bounded action candidates such as click, select, type, and done. It maps those candidates to single vocabulary tokens, scores them with one forward pass, and dispatches the selected browser action instead of generating CSS selectors, XPath expressions, or Playwright code. Text generation is used specifically for typing into fields, while structural actions use discrete logits scoring. The runtime also includes page-settling waits, visibility and occlusion checks, DOM-freshness checks, read-only protection, immutable execution traces, and external URL, title, and text assertions for outcome verification. The project provides a command-line interface, a Python API, and installable agent-skill integration, using Playwright Chromium for browser execution. It supports offline model operation after local weights are downloaded and is released under the MIT License.

HyperFrames is an open-source framework for turning HTML, CSS, media, and seekable animations into deterministic MP4 videos. It can be used locally through a CLI, by AI coding agents through skills, or as a rendering core for hosted authoring workflows. Compositions are defined as HTML with data attributes for timing, tracks, media, and sub-compositions. The renderer seeks each frame in headless Chrome, uses animation adapters such as GSAP, CSS, Lottie, Three.js, Anime.js, or WAAPI, and encodes the result with FFmpeg; its toolchain includes preview, linting, inspection, local rendering, browser-based editing, reusable catalog components, and AWS Lambda rendering. The project requires Node.js 22 or newer and FFmpeg, does not require React or a build step, and is licensed under Apache 2.0. Its agent skills support workflows including product videos, explainers, pull-request videos, captions, motion graphics, slideshows, music-driven videos, and general compositions.