This guide explains the simple structure of a Claude Skill, where to place the SKILL.md file, how to write effective front‑matter, use commands, parameters and dynamic injection, and share skills across a team, turning repetitive prompts into reusable, on‑demand actions.
The article explains what Agent Skills are, how to structure a SKILL.md file, the essential metadata, naming rules, description guidelines, common pitfalls, context limits, freedom levels, progressive loading, workflow design, and provides concrete open‑source examples and code snippets for writing effective Claude Skills.
The article explains what Agent Skills are, why a long SKILL.md should not be treated as a simple prompt or README, and provides concrete guidelines, metadata rules, example structures, freedom‑degree choices, progressive disclosure techniques, and common pitfalls for writing effective Claude Skills.
This guide explains all 14+ metadata fields available in a SKILL.md file, distinguishes the six standard Agent Skills fields from Claude Code extensions, and provides concrete examples and best‑practice recommendations for naming, descriptions, licensing, compatibility, allowed tools, and advanced options such as model selection and sub‑agent configuration.
The article explains Anthropic's official 5K‑token limit for SKILL.md files, breaks down the three‑level loading architecture, demonstrates progressive disclosure with concrete token calculations, and provides a step‑by‑step refactoring guide that reduces token usage while improving skill accuracy.
Agent Skills is an open‑source standard that defines reusable SKILL.md packages, a unified directory layout, and a progressive‑disclosure workflow, enabling AI agents across tools such as Antigravity to automatically discover, activate, and execute shared capabilities for faster, more consistent automation.
This article explains what Agent Skills are, shows the folder layout and SKILL.md format, introduces the progressive‑disclosure design, provides concrete best‑practice tips, testing and evaluation methods, and demonstrates how to package scripts for reliable AI‑assistant automation.
This guide explains the concept of LLM "Skills", shows how to organize skill directories for Claude and Copilot, walks through creating a "prepare‑pr" skill with a SKILL.md file, integrates Bash scripts for git checks, and demonstrates testing and extending the skill with additional checks and templates.
This article compares Skill.md and Agent Tools, explaining why AI agents need structured playbooks rather than just toolkits, outlining five key problems Skill.md solves, and showing how progressive disclosure and portable skill packages enhance context, compliance, and efficiency.
MOLTBOOK is an AI‑only forum where agents register, post, and interact via API calls using skill.md files, turning a Reddit‑like UI into a supply‑chain‑style automation platform; the article examines its architecture, the security risks of unsigned skill files and heartbeat mechanisms, and offers hardening guidelines for safe integration.
Claude’s new Agent Skills let developers package domain expertise into organized SKILL.md files and resource folders, enabling progressive disclosure, code execution, and scalable context loading, with detailed guidance on structure, bundling, evaluation, and security considerations for building robust, reusable AI agents.
