Total 56,145 skills, AI & Machine Learning has 9349 skills
Showing 12 of 9349 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.
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
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.
Review and analyze a skill against best practices for length, intent scope, and trigger patterns
Use this skill when the user requests to generate, create, or write professional research reports including but not limited to market analysis, consumer insights, brand analysis, financial analysis, industry research, competitive intelligence, investment due diligence, or any consulting-grade analytical report. This skill operates in two phases — (1) generating a structured analysis framework with chapter skeleton, data query requirements, and analysis logic, and (2) after data collection by other skills, producing the final consulting-grade report with structured narratives, embedded charts, and strategic insights.
Deploy and operate production agent servers with LangSmith Deployment. Use when work involves choosing Cloud vs Hybrid/Self-hosted-with-control-plane vs Standalone, preparing/validating langgraph.json, creating deployments or revisions, rolling back revisions, wiring CI/CD to control-plane APIs, configuring environment variables and secrets, setting monitoring/alerts/webhooks, or troubleshooting deployment/runtime/scaling issues for LangChain/LangGraph applications.