Agent Skill

AI Development Guide1/15/25...About 2 min

Core Concepts: What Are Agent Skills?

Agent Skills are standardized folder structures that bundle instructions, scripts, templates, and assets for specific tasks. At their core, they represent portable, programmatic knowledge.

Standard Components

SKILL.md: The core file containing YAML metadata (name, description) and detailed instructions in Markdown
scripts/: Executable scripts (Python, Bash, etc.) for handling complex logic
references/: Static reference materials or documentation
assets/: Output templates (LaTeX, HTML), images, or logos

Open Standard

A Skill you write can run seamlessly across Claude.ai, Claude Desktop, Claude Code, Claude Agent SDK, and even Codex, Gemini CLI, or any other platform that supports this standard.

Key Technical Features

Let's explore why Skills are more efficient than long prompts:

1. Progressive Disclosure

To protect the precious Context Window, Skills follow a load-on-demand principle:

State	Description
Initial	The model only loads the Skill's name and description
Triggered	When user intent matches the description, the model loads the main `SKILL.md` content
Deep Load	Only when necessary does the model read reference files or execute scripts

This prevents context pollution and significantly reduces hallucination risks in long conversations.

2. Deterministic Workflows

While LLMs are non-deterministic, business logic often requires consistency. With Skills, you can define strict SOPs:

Low vs. High Freedom: You can force the model to follow step-by-step instructions (Step 1, Step 2...) ensuring output formats (like specific CSV structures or PPT styles) remain consistent every time

Ecosystem: Skills, MCP, and Sub-agents

Component	Role	Function
MCP	Data Interface	Connects to external data sources (BigQuery, Notion, Google Drive)
Tools	Building Blocks	Provides foundational capabilities (Bash execution, file I/O)
Skills	Domain Experts	Guide the model on "how to use tools" for specific tasks (e.g., brand analysis)
Sub-agents	Parallel Execution	Independent execution units with their own context, assignable specific skills

Essential Tool: Skill Creator

The course highlights skill-creator — a "meta-skill" that uses AI to generate skills.

It includes Python scripts for initializing Skill structures, packaging files, and validation
Best Practice: Don't start from scratch with Markdown. Discuss your needs with Claude first, then let it invoke skill-creator to generate production-ready Skills

Cross-Platform Implementation

Here's how Skills perform across different environments:

Platform	Use Case
Claude.ai	Upload a `.zip` package to enable the web version to handle specific report formats
Claude API	Remote Skill invocation via API with `code_execution` preview capabilities
Claude Code	Automate development workflows (code reviews, test generation) via the `.claude/skills` directory
Agent SDK	Build complex applications like "Research Assistants" where a main agent coordinates Sub-agents with specialized skills (Search, Repo Analysis, Document Reading)

Developer Takeaways

Shift from "Writing Prompts" to "Packaging Skills": If you find yourself typing the same repetitive instructions, it's time to package them into a Skill
Build Your Private Skill Library: Create domain-specific skills for your business — like "Architecture Review" or "React Component Refactoring" — and migrate them quickly across projects
Embrace Standardization: Agent Skills mark the evolution of agent development from "prompt tinkering" to engineering governance