Total 56,724 skills, AI & Machine Learning has 9434 skills
Showing 12 of 9434 skills
MCP (Model Context Protocol) server build and evaluation guide, including local conventions for tool surfaces, config, and testing
AI agents: autonomous agents, multi-agent systems, LangChain, LlamaIndex, MCP.
Reduce your AI API bill. Use when AI costs are too high, API calls are too expensive, you want to use cheaper models, optimize token usage, reduce LLM spending, route easy questions to cheap models, or make your AI feature more cost-effective. Covers DSPy cost optimization — cheaper models, smart routing, per-module LMs, fine-tuning, caching, and prompt reduction.
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.
Principal backend engineering intelligence for Python AI/ML systems. Actions: plan, design, build, implement, review, fix, optimize, refactor, debug, secure, scale ML services and pipelines. Focus: data quality, reproducibility, reliability, performance, security, observability, model evaluation, MLOps.
Personal journal intelligence that transforms raw, unorganized thoughts into structured diary entries with psychological analysis. Use when the user provides journal entries, diary text, stream-of-consciousness writing, voice memo transcriptions, or asks to process daily thoughts into a structured format. Produces narrative entries, gratitude extraction, multi-level psychological analysis (surface/medium/clinical), health pattern flags, therapeutic micro-actions, and bridge-to-tomorrow planning. Trigger phrases: 'journal entry', 'diary entry', 'process my thoughts', 'Chronicle', 'daily reflection', 'write up my day'.
Generate fashion model imagery, virtual try-on, runway videos, and campaign visuals using EachLabs AI. Use when the user needs fashion content, model photography, or virtual try-on.
Use when designing futuristic agentic workflows, when wanting AI to proactively act on team communications, or when eliminating the bottleneck of formal specifications
Create clever, non-offensive trash talk. Rivalry-specific references, historical callbacks, memes. Fun, not mean.
Use when managing Ralph orchestration loops, analyzing diagnostic data, debugging hat selection, investigating backpressure, or performing post-mortem analysis
Adaptive multi-agent framework for automated data science tasks with planning, execution, and validation
Build and deploy autonomous AI agents with CowAgent - planning, memory, knowledge base, skills, and multi-channel support