1592 related articles

Deep dive into Agent skill routing: comparing pure model vs. pure retrieval approaches, with a detailed two-stage layered architecture balancing accuracy, latency, and cost.

A deep dive into AI Agent Skills: understand the core concepts and technical implementation through the four key elements — SKILL.md, references, scripts, and assets — and learn how Skills differ from prompts.

A deep dive into AI Agent Skills: their core concepts, technical implementation, the four key elements (SKILL.md, references, scripts, assets), and how Skills differ from prompts.

Agent Skills is a lightweight open-source format that extends AI agent capabilities with plug-and-play skill packages. This article dives deep into the Skills architecture, progressive disclosure, and how it differs from Multi-Agent design.

Agent Skills is a lightweight open-source format that extends AI agent capabilities via plug-and-play skill packages. Learn its architecture, progressive disclosure, and how it differs from Multi-Agent.

MCP and Skills aren't alternatives — they occupy different layers of AI Agent architecture. This article breaks down Function Call, MCP, and Skills to clarify each layer's role.

A deep dive into Anthropic's Agent Skills architecture — clarifying its difference from MCP, and how modular Skill packages enable scalable, maintainable enterprise agent development.

A security researcher demonstrates how to customize Claude into an automated penetration testing system with memory, skills, and a knowledge base — successfully compromising CTF targets and finding real Bug Bounty vulnerabilities.

MCP Server vs Agent Skills: how to choose? This article systematically outlines an AI Agent architecture decision framework across three dimensions—essential differences, applicable scenarios, and judgment criteria.

Harness Engineering is becoming a must-have skill for AI agent developer roles. Learn the architecture, how top agent products use it, and how to practice with LangChain DeepAgents.

Learn how to build an AI-driven API automation testing framework using Agent+Skill architecture with Claude Code, covering test case generation, script execution, and report output.

A deep dive into Agent Skills architecture: core concepts, components, and how it works. Clarifies common misconceptions about Skills vs. MCP, and compares Skills with Multi-Agent architecture.

Deep dive into enterprise AI agent architecture covering HARIS task decomposition, sandbox isolation, Skill persistence, MCP tool integration, and user-level memory systems.

Deep dive into Anthropic's Agent Skills architecture: modular skill loading, core concepts, enterprise value, and how it fundamentally differs from MCP.

Deep dive into how Skill and MCP collaborate in Agent engineering. Skills handle business logic loops while MCP provides standardized connectivity, forming the core of modern four-layer Agent architecture.

Deep dive into how Skill and MCP work together in Agent engineering. Skill handles business logic; MCP provides standardized connections. Together they form the core of modern Agent architecture.
TutorialsDeep dive into an open-source multi-Agent diagnostic system built on modified OneCall, featuring MCP real-time interaction, RAG-enhanced Q&A, and Skill routing to minimize Token consumption.
TutorialsDeep dive into OpenClaw's industrial-grade Agent architecture with its three-layer design, pluggable Skills system, and memory management. Includes a step-by-step LangChain reproduction guide with an enterprise HR assistant example.
TutorialsHow frontend engineers can move beyond API calls to build production AI systems — covering streaming output, BFF layers, RAG pipelines, and Agent orchestration with LangChain.js/LangGraph.js.
Deep DivesExplore NVIDIA's Deep Research Skill approach for embedding deep research capabilities as skill modules into AI Agent frameworks like Claude Code and LangChain, enabling goal decomposition, multi-source retrieval, and knowledge synthesis.