Total 44,222 skills, AI & Machine Learning has 7033 skills
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Write structured VGL (Visual Generation Language) JSON prompts for Bria's FIBO image generation models. Use this skill when creating detailed image descriptions in JSON format for text-to-image generation, image editing, inpainting, outpainting, background generation, or captioning. Triggers include requests to write structured prompts, create VGL JSON, describe images for AI generation, or work with Bria/FIBO's structured_prompt format. Also use when converting natural language image requests into the deterministic JSON schema required by FIBO models.
Use when generating visual assets with Bria.ai - product photos, hero images, icons, backgrounds. Includes batch generation (multiple images concurrently), pipeline workflows (generate → edit → remove background), and parallel API patterns. Use for websites, presentations, e-commerce catalogs, or any task needing multiple AI-generated images.
Generate and edit high-quality images using Gemini 2.5 Flash Image and Gemini 3 Pro Image (Nano Banana). Supports Text-to-Image, Style Transfer, Virtual Try-On, and Character Consistency.
Error pattern analysis and troubleshooting for Claude Code sessions. Use when handling errors, fixing failures, troubleshooting issues.
Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, constructing context from retrieved documents, adding citations, or implementing hybrid search.
Translate text between English and Indian languages using Sarvam AI's Mayura model. Use when the user needs to translate content, localize applications, or convert text between Hindi, Tamil, Bengali, Telugu, and 7 other Indian languages. Supports bidirectional translation, script control, and code-mixed text.
OpenAI API via curl. Use this skill for GPT chat completions, DALL-E image generation, Whisper audio transcription, embeddings, and text-to-speech.
External persistent memory for cross-session knowledge. Use when storing error patterns, retrieving learned solutions, managing causal memory chains, or persisting project knowledge.
Verify and validate AI output before it reaches users. Use when you need guardrails, output validation, safety checks, content filtering, fact-checking AI responses, catching hallucinations, preventing bad outputs, quality gates, or ensuring AI responses meet your standards before shipping them. Covers DSPy assertions, verification patterns, and generate-then-filter pipelines.
Amazon Bedrock Knowledge Bases for RAG (Retrieval-Augmented Generation). Create knowledge bases with vector stores, ingest data from S3/web/Confluence/SharePoint, configure chunking strategies, query with retrieve and generate APIs, manage sessions. Use when building RAG applications, implementing semantic search, creating document Q&A systems, integrating knowledge bases with agents, optimizing chunking for accuracy, or querying enterprise knowledge.
Automated job applications with AI-powered resume tailoring, cover letters, and recruiter outreach via email and LinkedIn.
Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.