Skill UI

Enforces full, unabridged code and document generation by overriding LLM truncation safeguards, forbidding placeholder patterns, and managing token-limit splits so every requested deliverable is returned complete.

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.

Transforms user articles, reports, or documentation into natural two-host conversational podcasts by building structured JSON scripts and running the bundled TTS pipeline to emit MP3 audio plus transcripts.

Generates professional PowerPoint decks by planning slide structure, crafting AI images for each slide, and composing them into a consistent, visually rich presentation file.

This skill creates high-quality videos from structured JSON prompts and optional reference images, then runs the prescribed Python script to produce MP4 output tailored to the requested scene, style, and technical specs.

This skill guides the generation of a complete, production-ready Model Context Protocol (MCP) server using C# and .NET. It covers advanced architectural patterns, including Host builder setup, proper dependency injection, structured logging, and implementing robust functional tools. Ideal for developers building sophisticated AI agents or backend services that require standardized communication and tool invocation capabilities.

A powerful tool leveraging OpenRouter and the Gemini 3 Pro Image model to create, modify, and composite high-quality images. Supports three primary use cases: prompt-only generation from text, detailed single-image edits (inpainting/outpainting), and complex multi-image composition. Users can specify resolutions up to 4K, making it suitable for professional creative and design workflows.

This skill is designed to manage complex, multi-step tasks by coordinating the efforts of multiple specialized AI agents. It provides structured methods for listing available agents, initiating real-time conversations, submitting complex background tasks (such as data analysis or report generation), tracking task status, and maintaining conversational context using session IDs. It is essential when a core task requires diverse expert knowledge or sequential collaboration.

This technique is designed for entity recognition and hypothesis generation when identifying Indian or Bollywood actors based on indirect clues. Instead of running broad searches, users should hypothesize a small set of candidate names (1-3) using the provided clues (e.g., awards, family history, controversies). Subsequently, targeted verification searches must be executed for each constraint against the candidate names to confirm the correct identity.

Hypogenic automates LLM-driven hypothesis generation and testing over tabular datasets, blending literature insights with empirical analysis to accelerate discovery in domains like deception detection or AI content evaluation.

Provides AI-ready drug discovery datasets, splits, and benchmarks covering ADME, toxicity, DTI, DDI, and molecular generation so researchers can train, compare, and optimize therapeutic ML models with curated splits and oracles.

A comprehensive skill for leveraging massive pre-trained transformer models across diverse AI domains, including Natural Language Processing (NLP), Computer Vision (CV), and Audio. Use this skill for advanced tasks such as text generation, classification, question answering, summarization, object detection, and model fine-tuning on proprietary datasets. It provides streamlined pipelines and granular control for deployment.