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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.

Deep dive into Anthropic's Agent Skills mechanism, explaining how Progressive Disclosure solves MCP context bloat and tool calling accuracy issues in AI agents.

A deep dive into Agent Skills architecture: modular design, progressive disclosure mechanism, and how it differs from Multi-Agent systems for AI capability extension.

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 lets AI agents extend professional capabilities on demand, like loading plugins. Learn what Agent Skills are, the problems they solve, and their modular advantages.

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.

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.

A Google DeepMind engineer reveals that over 50,000 AI agent skills come with almost no evals. Learn how to write skill evaluations, from description tuning to test design.

A Google DeepMind engineer reveals that over 50,000 AI agent skills come with almost no evals. This guide covers skill descriptions, test design, eval harnesses, and retirement strategies.

An in-depth look at how AI Agents execute tasks: clarifying the difference between Tools and Skills, and reconstructing the complete eight-step flow from understanding goals to delivering results.

A deep dive into how AI Agents execute tasks: clarifying the core difference between Tools and Skills, and reconstructing the complete eight-step execution flow from understanding goals to delivering results.

A recursive technical proposition: Can we build a "meta-Skill" that auto-transforms any Skill into a Dify workflow? This article dissects the boundary between deterministic orchestration and autonomous Agent decisions.
GitHub Daily · July 21: The Agent Skil…
GitHub Trending July 21: The Agent Skills ecosystem explodes as pluggable skill packs top the charts, MCP becomes the de facto standard, and ai-agent-book surges 4,434 stars in a day.

Andrew Ng's DeepLearning.ai teams up with Anthropic to teach Agent Skills: file structure, progressive disclosure, MCP integration, and the full path from Claude.ai to the Agent SDK.

Google DeepMind engineer Philip reveals: almost everyone uses coding agent Skills, yet almost no one writes evals for them. A deep dive into Skill evaluation methods, 8 actionable tips, and a real Gemini API case study.

A deep dive into Agent Skills: what they are, how they differ from Function Calling, and a 3-step guide to understanding and customizing Skills for real business use cases.
Fine-Tuning Cosmos Models in One Day w…
NVIDIA uses Autonomous Coding Agents and Agent Skills with TAO to fine-tune Cosmos visual reasoning models in one day, achieving over 90% accuracy.

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.