#Skill MCP difference
256 related articles
·4 min
Hands-On Skill Writing and Agent Testing: A Guide to AI Testing Transformation
An in-depth look at AI testing challenges. Learn to write reusable Skill packs and master Agent testing and LLM evaluation—covering the SKILL.md six-dimensional rule, skill-creator, EvalScope, and dataset selection.
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·5 min
From Chat to Agent: Automating Your Entire Business Workflow with AI Agents
Veteran AI practitioner Remy breaks down the leap from chat models to AI agents: how agents work, the three pillars of context, tools, and skills, MCP connections, and hands-on architecture to make you a 100x employee.
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·3 min
Understand Anything: The AI Skill That Turns Code into Interactive Knowledge Graphs
Understand Anything is a high-star open-source GitHub skill that runs static analysis on any codebase and generates interactive knowledge graphs. It supports Claude Code, Cursor, Copilot and other agents, letting engineers ask questions in natural language with path references.
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·3 min
Understand Anything: The AI Skill That Turns Code into an Interactive Knowledge Graph
Understand Anything is a high-star open-source GitHub skill that performs static analysis on any codebase to generate an interactive knowledge graph, supporting Claude Code, Cursor, Copilot and more.
Read more →
·3 min
Understand Anything: The AI Skill That Turns Code into an Interactive Knowledge Graph
Understand Anything is a high-star open-source GitHub skill that performs static analysis on any codebase to generate interactive knowledge graphs, supporting Claude Code, Cursor, Copilot and more.
Read more →
·2 min
Agent Skills Explained: Giving AI Plug-and-Play Capability Packs
Agent Skills is a lightweight open-source format that lets AI agents extend professional capabilities on demand, like loading plugins. Learn what Agent Skills are, the problems they solve, and their modular advantages.
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·2 min
DeepAgents in Practice: A Deep Dive into Sandbox Backends and Agent Skills
A deep dive into DeepAgents' sandbox backend and Agent Skills: why Agents need sandboxes to isolate code execution, how Skills enable modular capability reuse, and how the two work together to build reliable AI Agent systems.
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·2 min
DeepAgents in Practice: A Deep Dive into Sandbox Backends and Agent Skills
A deep dive into DeepAgents' sandbox backend and Agent Skills: why Agents need sandbox isolation to run code, how Skills enable modular capability reuse, and how the two combine to build reliable AI Agent systems.
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·3 min
Pi Agent Configuration Guide: Building Your Own AI Coding Assistant
A step-by-step Pi Agent configuration tutorial covering installation, LLM connection, extension ecosystem, MCP setup, and Token-saving tips. Learn to build a truly controllable AI coding assistant.
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·3 min
Context Engineering: Why Does More Context Make AI Dumber?
Anthropic introduces Context Engineering, revealing Context Rot: the more tokens in the window, the worse AI retrieval accuracy. Learn the three principles, just-in-time retrieval, and three moves against context overflow.
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·3 min
The AI Coding Landscape: Model Tiers, Tool Camps, and a Deep Dive into MCP/Skills/CLI
A systematic map of today's AI coding landscape: the evolution from ChatGPT to Claude Code, LLM capability tiers, tool camps like Cursor/Copilot, and the three key weapons of the Agent era — MCP, Skills, and CLI.
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·3 min
Claude Code for Absolute Beginners: A Step-by-Step Guide (Install + Connect an LLM + Hands-On Practice)
How do complete beginners get started with Claude Code? This guide covers VS Code setup, two ways to connect an LLM in China, four core usage modes, and building your first practical tool without writing a single line of code.
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·2 min
Getting Started with Claude Code: A Complete Guide to Installation, Configuration, and Git Workflows
An in-depth guide to Claude Code from installation to hands-on practice: CLI setup, switching to domestic LLMs (CC Switch tool), conversational Git workflows, plus project analysis and automated bug fixing tips for AI-powered coding.
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·8 min
A Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.
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·8 min
The Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.
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·4 min
Spring AI 1.0 Practical Guide: A Java Developer's Fast Track to Building AI Applications
Spring AI 1.0 is here — Java developers can now build AI apps without switching to Python. This guide covers LLM integration, RAG, intelligent customer service, and Agent patterns for enterprise deployment.
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·3 min
AI Not Working? Learn to Diagnose Which Layer Is the Problem — Loop, Harness, or Context
AI agents underperforming? The root cause usually isn't the model. This guide breaks down Loop, Harness, and Context Engineering so you can diagnose the real issue fast.
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·6 min
The AI Builder's Handbook: A Complete Guide to LLM Principles, RAG Architecture, and Agent Design
From the autocomplete nature of LLMs, tokens, and context windows to RAG vector databases, the MCP protocol, and AI agent loop design — this article uses vivid analogies to unpack the reality of AI engineering.
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·2 min
MCP for Beginners: The Essential Protocol for AI Agent Development
Learn what MCP (Model Context Protocol) is, why it's replacing Function Calling, and how it breaks AI data silos to enable remote tool invocation for agents.
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·4 min
Cross-Platform AI Agent Setup Guide: Breaking Free from Vendor Lock-In for Good
Model performance gaps are closing. Real competitive advantage lies in portable AI agent architecture. Learn how to build a workspace that works across Claude Code, Codex, and beyond — no vendor lock-in.
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