Total 57,111 skills, AI & Machine Learning has 9502 skills
Showing 12 of 9502 skills
CLI for Limitless.ai Pendant with lifelog management, FalkorDBLite semantic graph, vector embeddings, and DAG pipelines. Use for personal memory queries, semantic search across lifelogs/chats/persons/topics, entity extraction, and knowledge graph operations. Triggers include "lifelog", "pendant", "limitless", "personal memory", "semantic search", "graph query", "extraction".
Build production-ready MCP clients in TypeScript or Python. Handles connection lifecycle, transport abstraction, tool orchestration, security, and error handling. Use for integrating LLM applications with MCP servers.
Build MCP (Model Context Protocol) servers using the official Python SDK. Covers FastMCP high-level API with @mcp.tool(), @mcp.resource(), @mcp.prompt() decorators, FastAPI/Starlette integration, transports (stdio, SSE, streamable-http), and database integration.
Use when user asks to leverage claude or claude code to do something (e.g. implement a feature design or review codes, etc). Provides non-interactive automation mode for hands-off task execution without approval prompts.
Create analytical archival summaries of AI conversations, capturing intellectual journeys, key insights, and technical logs. Use when archiving, saving, or documenting a chat session.
Phase coordination, agent handoffs, and workflow state machine management
Compares old vs new prompts across test cases with diff summaries, stability metrics, breakage analysis, and fix suggestions. Use for "prompt testing", "A/B testing prompts", "prompt versioning", or "quality regression".
Design multi-skill workflow systems with artifact-based state handoff. Use when building skill pipelines, sequenced workflows, or when "workflow system", "skill pipeline", "state handoff", or "artifacts" are mentioned.
Upscales an image using AI super-resolution to increase resolution with detail generation. Use when you need to enlarge images, improve low-resolution photos, or prepare images for large-format display.
Use when "deploying ML models", "MLOps", "model serving", "feature stores", "model monitoring", or asking about "PyTorch deployment", "TensorFlow production", "RAG systems", "LLM integration", "ML infrastructure"
Generate images via Krea.ai API (Flux, Imagen, Ideogram, Seedream, etc.)
Digital archiving workflows with AI enrichment, entity extraction, and knowledge graph construction. Use when building content archives, implementing AI-powered categorization, extracting entities and relationships, or integrating multiple data sources. Covers patterns from the Jay Rosen Digital Archive project.