Total 57,191 skills, AI & Machine Learning has 9512 skills
Showing 12 of 9512 skills
Template-based AI prompt engine with YAML templates, brand kit injection, input sanitization for security, and token-efficient context blocks.
LLMs, prompt engineering, RAG systems, LangChain, and AI application development
Observe user interaction patterns, extract per-session facets, update a dual-matrix soul state, and periodically synthesize a personalized Soul profile for better collaboration.
Execute Python code locally with marketplace API access for 90%+ token savings on bulk operations. Activates when user requests bulk operations (10+ files), complex multi-step workflows, iterative processing, or mentions efficiency/performance.
This skill should be used when the user asks to "fine-tune a DSPy model", "distill a program into weights", "use BootstrapFinetune", "create a student model", "reduce inference costs with fine-tuning", mentions "model distillation", "teacher-student training", or wants to deploy a DSPy program as fine-tuned weights for production efficiency.
Create a new skill that uses an MCP server, following best practices from the MCP CLI guide. Use when user wants to create a skill for a new MCP server or integrate MCP functionality into a skill.
Build full-stack web applications powered by Google Gemini's Nano Banana & Nano Banana Pro image generation APIs. Use when creating Next.js image generators, editors, galleries, or any web app that integrates gemini-2.5-flash-image or gemini-3-pro-image-preview models. Covers React components, server actions, API routes, storage, rate limiting, and production deployment patterns.
Evaluate and improve Claude Code commands, skills, and agents. Use when testing prompt effectiveness, validating context engineering choices, or measuring improvement quality.
Illustre automatiquement le journal d'une aventure BFRPG en générant des images pour les moments clés (combats, explorations, découvertes). Utilise la génération parallèle pour une performance optimale.
Build RAG systems - embeddings, vector stores, chunking, and retrieval optimization
USE FOR AI-grounded answers via OpenAI-compatible /chat/completions. Two modes: single-search (fast) or deep research (enable_research=true, thorough multi-search). Streaming/blocking. Citations.
This skill should be used when the user has a completed implementation plan (plan.md) and is ready to execute the tasks defined therein. Actively uses Agent Teams or subagents to execute batches of independent tasks in parallel, following BDD/TDD principles.