171 related articles
Claude Code Skills Encapsulation: Maki…
Learn how to encapsulate Claude Code Agent Skills for test case design. Solve prompt repetition pain points with on-demand loading and skill reuse techniques.
Deep DivesDeep breakdown of AI Agent Skill's three-layer architecture: decision layer dynamic routing, encapsulation layer SOP standardization, and execution layer state machine self-healing, with practical solutions for context explosion, error recovery, and generality balance.

Deep dive into Google's open-source google/skills project with 16,000+ GitHub stars—an official AI Agent skill library providing standardized capability modules for the Google ecosystem.

A six-run task-size benchmark tests whether Codex Skills actually save tokens. Data reveals cost-benefit performance across different task complexities.

Deep dive into Driven, the AI investment agent that connects the entire research-to-execution pipeline through 260+ API integrations, custom Skills, and Playbooks.

From HTML readability to code reuse dilemmas and framework lock-in risks, a systematic analysis of Tailwind CSS controversies to help developers make informed technology choices.

ComfyUI's Subgraphs update breaks image upload and sampler preview, paralyzing user workflows. Analysis of the community backlash and lessons for open-source AI tools.

Complete guide for backend developers transitioning to AI/LLM engineering. Covers the 4 core skills—Python, RAG, Fine-tuning, and Agents—with a phased learning roadmap and practical project advice.

Complete guide to Pi coding agent: design philosophy, installation, shortcuts, session management, and 7-layer customization architecture. How this 45K-star minimalist terminal tool redefines AI coding workflows.

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.

A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.

Analysis of MVTec Merlic's capabilities for robot pick-and-place tasks, comparing it with Halcon for hand-eye calibration and 3D pose estimation, with practical selection guidance.

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.

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.

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.

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.

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.

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.

A systematic breakdown of the three mainstream test automation approaches in the AI era: AI-generated code scripts, DOM parsing driven, and LVM visual model driven. In-depth comparison of principles, pros/cons, and use cases.