Previously we checked how to cook AGENTS.md, today we'll check another important part of agent configuration - skills.
Agent skill is a detailed workflow description or checklist for performing a specific task. Technically a skill is a folder containing a `SKILL.md` file, scripts, and additional resources. Most imprtantly, it's a standard already supported by different AI agents.
Skills structure in a repo:
skills/
├──my-skill/
├── SKILL.md # Required: instructions + metadata
├── scripts/ # Optional: executable code
├── references/ # Optional: documentation
└── assets/ # Optional: templates, resources
SKILL.md is a standard md file used to define and document agent capabilities. It consists of:
- Metadata (~100 tokens):
name(skill name) and description (when to use).- Instructions (< 5000 tokens recommended): The main part of the file that is loaded when the skill is activated.
The overall flow is as follows::
1. Discovery: At startup the agent loads the name and description of each available skill.
2. Activation: When a task matches a skill’s description, the agent reads the full `SKILL.md` instructions into context.
3. Execution: The agent follows the instructions, loading referenced files or executing bundled code if needed.
The main idea is to load instructions lazily to prevent prompt sprawl and context rot, when LLMs lose focus on specific tasks and start making mistakes.
What I like about skills is that it's an artifact with clear specification and development lifecycle. It allows not only collecting knowledge about tools and procedures, but also makes AI outputs more testable and predictable.
#ai #agents #engineering #documentation