Anthropic has released a guide detailing “Skills,” a new method for customizing Claude by teaching it specific tasks through dedicated folders containing structured metadata in a single SKILL.md file. Skills enable consistent automation of workflows, enhancement of existing tools via accumulated expertise, and standardized document creation, functioning alongside MCP (which grants Claude tool access). The guide highlights five effective patterns – sequential orchestration, multi-tool coordination, iterative refinement, context-aware tool selection, and domain-specific intelligence – while cautioning against vague descriptions, overly complex skills, and lack of error handling. Ultimately, Skills aim to transform Claude from a general chatbot into a focused, integral part of daily work processes.
This article discusses the impact of Anthropic's Claude Code, an AI agent that is significantly impacting software development and the broader information work economy. It analyzes Claude Code's capabilities, its potential to drive revenue growth for Anthropic, the challenges it poses for Microsoft, and the shift in competition within the AI landscape.
Anthropic is rolling out a significant update to Claude Code, merging slash commands into a more powerful 'Skills' system. This allows for custom workflows and integrations directly within the Claude interface, enhancing its utility for developers and streamlining complex tasks. The update also includes improved code explanations and debugging features.
The article discusses the evolution from RAG (Retrieval-Augmented Generation) to 'context engineering' in the field of AI, particularly with the rise of agents. It explores how companies like Contextual AI are building platforms to manage context for AI agents and highlights the shift from prompt engineering to managing the entire context state.
A guide to supercharging Claude Code with Skills and the Model Context Protocol (MCP), including running Claude Code in an IDE like Cursor or VS Code. It covers setting up Skills, connecting to MCP servers, and combining both for powerful workflows.
Simon Willison’s annual review of the major trends, breakthroughs, and cultural moments in the large language model ecosystem in 2025, covering reasoning models, coding agents, CLI tools, Chinese open‑weight models, image editing, academic competition wins, and the rise of AI‑enabled browsers.
Over the last year, MCP accomplished a rapid rise to popularity that few other standards or technologies have achieved so quickly. This article details the unlikely rise of the Model Context Protocol (MCP) and its journey to becoming a generally accepted standard for AI connectivity.
LLM Council works together to answer your hardest questions. A local web app that uses OpenRouter to send queries to multiple LLMs, have them review/rank each other's work, and finally a Chairman LLM produces the final response.
This Gist contains the system prompt for Claude Code, Anthropic's CLI for Claude. It details the tool's purpose, instructions for use, tone, proactive behavior, code style guidelines, task management, and references.
An analysis of Claude's extensive system prompt, highlighting its components, including tool definitions, behavior instructions, and how it reflects Anthropic's development priorities. The article details changes between Claude 3.7 and 4.0, revealing a shift towards encouraging search functionality and addressing user-observed issues.
