AI-agent Skill for generating polished HTML slide decks: editorial magazine and Swiss layouts, image prompts, social covers, and a WebGL/low-power presentation runtime.
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Crypto Trading Bots in Python - Triangular Arbitrage, Beginner & Advanced Cryptocurrency Trading Bots Written in Python
Botright, the most advance undetected, fingerprint-changing, captcha-solving, open-source automation framework. Build on Playwright, its as easy to use as it is to extend your code. Solving your Captchas for free with AI.
Generate one image for an already established interactive-story turn.
The AMLSim project is intended to provide a multi-agent based simulator that generates synthetic banking transaction data together with a set of known money laundering patterns - mainly for the purpose of testing machine learning models and graph algorithms. We welcome you to enhance this effort since the data set related to money laundering is critical to advance detection capabilities of money laundering activities.
(WIP) Open Knowledge Layer(OpenKL): The Advance Knowledge and Memory for Personal Agents.
Execute plans and multi-step PR series end to end. Use when the user asks to implement or continue an existing plan, work a planned step, or when a monitored plan-series PR merges and its successor should advance automatically.
Use when an Agent needs to create, resume, advance, block, revise, complete, or abandon a durable current execution plan in LWC.
Use whenever writing, editing, or reviewing markup or UI code — HTML, JSX/TSX, Vue/Svelte/Angular templates, web components, email HTML, or CSS that affects text size, color, focus, motion, layout order, or hit area. Also use when adding a button, link, form, input, modal, dropdown, menu, tabs, tooltip, toast, icon, image, iframe, table, list, keyboard shortcut, drag interaction, or any click handler; when a design has to become code; and when the user says "accessibility", "a11y", "WCAG", "screen reader", "keyboard navigation", "focus", "aria", "contrast", "alt text", or "axe".
Turn a vague idea into a tight, format-specific outline through structured interrogation. Use when the user is stuck on structure, does not know what to write, or has a topic but no angle. Works for newsletters, sales pages, posts, scenes, and scripts.
Scientific research engine with adversarial review, tree search, and serendipity detection. Use when: exploring hypotheses, validating findings against literature, running computational experiments with quality gates, or hunting for unexpected discoveries. Do NOT use for simple Q&A, code editing, or non-research tasks.