Skill UI

An advanced AI agent designed to simulate Elon Musk with deep psychological and communicative fidelity. It applies first principles thinking, combines scientific reasoning (physics, engineering), and adopts his characteristic tone—including dry humor and candid opinions—for roleplay, strategic brainstorming, and complex problem-solving related to technology, space, and sustainable energy.

Simulates the persona of Geoffrey Hinton, a Turing Award winner and pioneer of deep learning. This skill adopts his first-person voice, combining deep technical knowledge (including backpropagation, deep belief networks, and Boltzmann machines) with academic rigor, epistemic humility, and characteristic British humor. It is ideal for in-depth discussions on the theoretical foundations, history, and principles of complex system learning in AI.

Creates high-fidelity visuals through structured JSON prompts and a Python generator script, handling subjects, styles, references, and technical specs for characters, scenes, or products.

This skill provides methods to optimize ElevenLabs usage costs for Text-to-Speech (TTS) workloads. It covers model selection (e.g., using Flash/Turbo for savings), implementing character-efficient text pre-processing to reduce character count, and setting up real-time quota monitoring with budget alerts. Ideal for developers managing high-volume, cost-sensitive voice applications.

Lambda is a compact, machine-native communication protocol specifically designed for agent-to-agent (A2A) messaging. It functions as a shared, unambiguous vocabulary built from 'atoms' (2-character codes), completely bypassing the need for human natural language interpretation. It is ideal for orchestrators, task delegation, and logging structured coordination signals (like heartbeats or state changes) in multi-agent systems. Crucially, Lambda is intended only for machine communication, not for user-facing dialogue.

This meta-skill manages the end-to-end generation of AI-powered short dramas from a given topic. It first drafts a detailed, shot-by-shot shooting script, pausing for user review and adjustments. After confirmation, it generates consistent visual assets (universal character identity and scene compositions) and renders the final video clips. The output includes the fully rendered MP4, subtitles, title cards, and the complete script file.

Generates high-quality, short video clips (3-15s) using the Seedance 2.0 model. It accepts structured English prompts, an optional starting frame image, and style/identity reference images to ensure character and visual continuity. Supports multiple cloud backends (OpenRouter, Volcengine, BytePlus), making it ideal for storyboarding, cinematic concept visualization, or short film pre-production.

A comprehensive guide for authors to determine the optimal conference venue for their speech-related research. It utilizes a 'modality test' to assess whether a contribution relies on audio signal characteristics (acoustics, prosody, etc.) or merely text transcriptions. The guide helps authors choose between major venues like INTERSPEECH, ACL, ICASSP, and specialized workshops, ensuring the claim is reviewed by relevant experts.

This meta-skill automates the entire short-drama production pipeline, starting from a simple topic. The workflow analyzes the request to infer render style, character identity, and shot count. It first drafts a detailed, shot-by-shot shooting script and pauses for user review. After approval, it generates a universal cast reference image, per-shot composition images, and corresponding video clips. Crucially, it maintains character and scene consistency by anchoring every video to both the reference image and the composition image. Finally, it adds title/ending cards, burns subtitles, and de...

This skill compiles user creative intent into executable image and video prompts for AI models. It specializes in character consistency, cinematic storyboards, and reference asset mapping for R2V/I2V/T2V tasks. It ensures visual contracts, narrative flow, and production-ready specifications without replacing model capabilities.

Splitting extracted text into optimal chunks for LLM context windows or RAG ingestion. Supports character and token-based sizing, multiple chunker types (text, markdown, yaml, semantic), and standalone CLI command.

Generate and edit images and videos using Google's Gemini media models (Nano Banana 2/Pro, Gemini Omni Flash) with cost-approval gates, reference-image support, and detailed logging per call. Supports on-brand generation from reference sets and multi-image fusion for consistent character series.