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Multi-agent investment research framework where fundamental, sentiment, news and technical analysts, bull and bear researchers, a trader and risk managers debate a stock and produce a report and rating. Covers US, Hong Kong and A-shares. Needs Python and an LLM API key; not investment advice.

Command-line edition of the open-source OpenBB investment research platform: query stock prices, financial statements, macroeconomic and other financial data from the terminal, and automate data pulls with Routine scripts. Officially maintained; some sources need API keys.

Write videos in HTML, CSS and frame-seekable animations, preview them from the CLI and render deterministic MP4s. Comes with agent skills for product launch videos, captions and talking-head re-edits. Maintained by HeyGen; needs Node.js 22+ and FFmpeg.

Multi-agent simulated hedge fund: agents modeled on investors like Buffett and Munger work with quant and risk modules to analyze stocks, with backtesting. Good for teaching investment frameworks. Needs Financial Datasets and model API keys; no real trading, not investment advice.

Open-source crypto trading framework: download market data, backtest and optimize strategies, and paper trade from the CLI while agents iterate on strategies. Docker recommended; strategies need Python and live trading needs exchange API keys. Backtests don't guarantee returns.

Microsoft's open-source AI quant investment research platform: the qrun command runs dataset building, model training, backtesting and evaluation from a YAML config, with many benchmark models. The official dataset is paused, so prepare market data per the README first.

Google Labs' DESIGN.md format and CLI: designers capture colors, typography and spacing in a file for agents; lint checks broken references and WCAG contrast, diff compares versions and export outputs design tokens for Tailwind and more. Needs Node.js; the format is in alpha.

Financial research terminal agent, like Claude Code for finance: breaks company research questions into steps, pulls financial statements and market data, and self-checks before answering. Needs Bun, a model API key and a Financial Datasets API key; for learning and research only.

Removes image backgrounds with one command: single images, whole folders or watched directories, mask-only output and switchable models like U2Net and SAM. Can also run as an HTTP server or process video frames with FFmpeg. Default models run locally.

SVG optimizer CLI and Node.js library: shrinks SVGs by removing editor metadata, comments, hidden elements and redundant attributes, processes whole directories recursively, and gives fine control through plugin config.

ML-based video upscaling and frame interpolation using Real-ESRGAN, Real-CUGAN, RIFE and other models to upscale old low-res video or raise frame rates; video2x handles one video per run and is scriptable. Needs a Vulkan GPU; Windows, Linux and Docker builds, no native macOS.

Command-line tool for bulk-downloading galleries and posts from many image hosts and social platforms, with flexible file naming and config, and yt-dlp integration for video. Main development has moved to Codeberg; the GitHub repo stays in sync.

Official Lark (Feishu) CLI with 200+ commands for messages, docs, Base, Sheets, calendar, mail, approvals, OKRs, meetings and Minutes, plus 20+ bundled lark-* agent skills and structured output. Create a Lark app and sign in first.

Veteran image processing CLI suite that converts, resizes, crops, composites and batch-processes JPEG, PNG, GIF, TIFF, PDF and many more formats, handy for agents handling images in scripts.

Fast, memory-efficient image processing library with a vips CLI for batch resizing, cropping, rotating, format conversion (WebP, AVIF, HEIC, TIFF and more) and thumbnails, handling very large images smoothly. Good for design and media teams processing assets in bulk. Install with Homebrew on macOS.

Batch-translates text in manga, posters and screenshots with one command: detects text, runs OCR, erases the original and typesets the translation back into the image. Japanese-focused, with 20+ languages supported. Install from source (Python 3.10+); offline models, DeepL or LLM APIs.

Removes backgrounds from images and videos with one AI command: batch whole folders, use a portrait model, refine edges or swap in a solid color, and output transparent MOV or composite video onto a new background. Runs locally; install PyTorch and ffmpeg first. Models download on first run.

Open-source font editor: fontforge -script runs Python scripts headlessly to batch-edit glyphs, convert between OTF, TTF, UFO and other formats, and generate fonts, for type design and font processing. Homebrew installs the CLI version; install the desktop app for the GUI.

Diffusion model inference in pure C/C++: one sd-cli command runs SD, FLUX, Qwen Image, Wan and more locally to create or edit images and short videos, with Metal acceleration on Mac. No cloud needed; bring your own model weights and use a release binary or build from source.

Converts raster images like JPG and PNG to SVG, handling color tracing, black-and-white line art and unevenly lit scans, for vectorizing logos, illustrations and old drawings. The CLI is a 1.0 preview installed with cargo (needs Rust); a desktop app is also available.

Command-line color tool: generate, mix, lighten and darken colors, convert between HEX, RGB, HSL, Lab and more, build gradients and sets of distinct colors, pick readable text colors for a background, and simulate color blindness. Install via Homebrew; no account or API key.

Live stock and crypto quotes in the terminal with portfolio profit and loss tracking, using Yahoo Finance and Coinbase data. The main view is an interactive dashboard; ticker print exports holdings from your config at current prices as JSON or CSV for scripts and agents.

Language and toolset for double-entry bookkeeping in text files: bean-check validates the ledger, bean-format normalizes it, and Fava or beanquery handle reports and queries. Plain-text ledgers are easy for agents to generate and keep in version control.

Lossy PNG compression CLI: converts images to 8-bit PNGs that keep transparency, usually 60-80% smaller, with batch processing and a quality range setting. Handy for slimming down web assets, slides and article images. Install via Homebrew on macOS; no account.