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Artificial Intelligence (AI) Agents Skills

Source: What AI Agent Skills Are and How They Work - IBM - YouTube with Martin Keen

Use case: AI agents are good at getting information, but weak at procedural knowledge like creating a financial report using 30 steps or how to ride a motorcycle in Rome Italy safely. Skills address this weakness by giving the agent the process to follow.

Skills answer what to do, the order to do them, and judgment. They teach an agent how to do a job (a repeatable task).

Creating a skill is creating a SKILL.md markdown file with name, description describing when the skill applies.

---
name: pdf-builder
description: Use when the user asks to extract a PDF
---
# PDF Builder
Instructions to agent, for example read content, run command to build PDF

Optional skill folders:

  • /scripts/
    • Programming language files agent can run like Python, bash, Java
  • /references/
    • Documentation
  • /assets/
    • Data files
    • Templates

Loading Skills using Progressive Disclosure

Section titled “Loading Skills using Progressive Disclosure”

Agent is given name and description of skills it has access to. Like an index of skills. This approach reduces context needed (reduce token use).

If agent finds a description that is useful, it will load the skill.md. Optional folders are only loaded when a task is required.

Knowledge: MCP, RAG, Fine tuning, and Skills

Section titled “Knowledge: MCP, RAG, Fine tuning, and Skills”

Open standard published at Agent Skills Overview - Agent Skills

my-skill/
├── SKILL.md # Required: metadata + instructions
├── scripts/ # Optional: executable code
├── references/ # Optional: documentation
├── assets/ # Optional: templates, resources
└── ... # Any additional files or directories

Semantic memory –> RAG

Episodic memory –> Conversation logs, interaction history

Procedural memory –> Skill files

Skills can have access to scripts that run on the user’s machine, environment variables, and secrets. Review skills before using them.