Total 51,037 skills, AI & Machine Learning has 8547 skills
Showing 12 of 8547 skills
Generate videos using Sora via lnapi.com.
Create realistic long-form AI talking head/UGC videos that don't look AI-generated. Use when user wants to make "realistic AI video", "UGC video", "talking head video", "AI spokesperson", "AI ad content", "video that looks real", "human-looking AI video". Orchestrates Nano Banana for base images and Kling AI for video generation with natural pacing.
Enterprise session state management, token budget optimization, runtime tracking, session handoff protocols, context continuity for Claude Sonnet 4.5 and Haiku 4.5 with context awareness features
Guide for conducting thorough and synthesized research, focusing on verification, multi-source analysis, and RAG patterns.
Guide for giving your AI agents capabilities through tools. Helps you identify what your AI needs to do, create tool definitions, and attach them in a way that makes sense for your framework.
Tool for creating and validating Agent Skills. Use when users want to create a new skill or manage existing skills. Supports initialization, validation, and iterative development workflows.
Generate AI videos using varg SDK React engine. Use when creating videos, animations, talking characters, slideshows, or social media content.
Analyze videos using Google's Gemini API - describe content, answer questions, transcribe audio with visual descriptions, reference timestamps, clip videos, and process YouTube URLs. Supports 9 video formats, multiple models (Gemini 2.5/2.0), and context windows up to 2M tokens (6 hours of video).
Assess research idea novelty through systematic literature search. Multi-round search-evaluate loops with harsh critic persona. Binary novel/not-novel decision with justification. Use before committing to a research direction.
Build LLM applications using Dify's visual workflow platform. Use when creating AI chatbots, implementing RAG pipelines, developing agents with tools, managing knowledge bases, deploying LLM apps, or building workflows with drag-and-drop. Supports hundreds of LLMs, Docker/Kubernetes deployment.
Use when implementation is complete, all tests pass, and the agent is operating inside a Grove workspace that needs to be resolved or cleaned up
Codebase mapping and documentation using parallel AI subagents. Invoke for: map this codebase, document architecture, understand codebase, onboarding to new project, create CODEBASE_MAP.md, generate architecture diagrams.