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Skills and Context Modules

Lola distributes two types of AI context packages: Agent Skills and AI Context Modules.

Agent Skill

An Agent Skill is a standalone context file following the AgentSkills.io standard. It is the fundamental unit of AI context - a markdown file (SKILL.md) with optional supporting assets that can be loaded by an agent on demand for In-Context Learning (ICL).

Agent Skills come in two forms:

Standalone — a single focused skill:

my-skill/
  SKILL.md              # Required: skill definition
  scripts/              # Optional: executable scripts
  reference/            # Optional: documentation
  assets/               # Optional: other supporting files

Skill Pack — multiple related skills grouped together:

my-skills/
  skills/
    skill-a/
      SKILL.md
    skill-b/
      SKILL.md

A skill injects context into the LLM's runtime memory, guiding it to return more precise results. It translates your workflows and knowledge into transferable instructions an agent can execute.

AI Context Module

An AI Context Module is a superset of a skill. It wraps one or more skills inside a module/ directory alongside additional assets:

my-project/
  module/                   # AI Module Directory
    AGENTS.md               # AI Main Spec
    commands/               # Assistant Commands
    mcps.json               # MCP Settings
    my-skill-A/             # Skill following agentskills.io
      SKILL.md
      scripts/
      reference/
      assets/
    my-skill-N/             # Another Skill
      SKILL.md
      scripts/
      reference/
      assets/

SKILLs are not everything. We also need MCP settings, agent personas, system prompts, commands, or custom bootstrap dependencies. The AI Context Module solves this by packaging an entire AI context - multiple skills plus all the supporting configuration - into a single distributable unit.

AI Context Modules also solve the problem where a developer wants to integrate their codebase with AI context. A module can live inside a project, allowing skills to reference scripts, functions, or assets from the codebase itself. This is useful when you want to mix your codebase with agent knowledge - inheriting bootstrap scripts or utility functions into skills and commands. In this way, AI Context Modules extend skills to provide AI knowledge at a broader project level.

When to Use Each

Agent Skill AI Context Module
Use case Single focused capability (standalone or skill pack) Complete agent context
Contents SKILL.md + optional assets; or skills/ directory with multiple skills Multiple skills + AGENTS.md + commands + MCP
Standard AgentSkills.io Lola extension of the standard
Example A code review skill, or a pack of review + lint + test skills A full DevSecOps module with review, security, and compliance skills
Init Manual or future lola skill init lola mod init

See Installing Modules for more details.

AI as Code

The vision behind AI Context Modules is AI as Code: agent settings, MCP configurations, skills, and context dependencies - all managed as code, versioned, and distributable as packages. With Lola, your entire AI agent context tree can be deployed and shared across teams and tools.