Skills in AI and Agentic Systems
Problems Across Individuals and Engineering Teams Today
One common problem is the lack of reusable skills and processes.
The context required to perform a task is often scattered across:
Prompts
Documents
Previous conversations
Individual knowledge and memory
As a result, the AI may be capable of performing the task, but the working context is not clear or consistently available.
For example, imagine having to review the PRDs (Product Requirement Documents) of 30 students.
Every time, you may need to provide the AI with the same instructions:
Check whether the problem statement is clear.
Identify missing functional and non-functional requirements.
Check edge cases.
Review technical feasibility.
Evaluate whether the scope is realistic.
Suggest improvements.
Create an HLD, LLD, and Technical Requirement Document with a proper implementation plan.
Instead of repeating these instructions every time, we can turn them into a Skill.
What is a Skill?
A skill is a reusable package of task-specific instructions.
Let's break this definition down.
1. Task-Specific Instructions
These are instructions that tell an AI how to perform a particular type of task.
For example, if we frequently ask an AI to review PRDs, we might define instructions such as:
Check whether the problem statement is clear.
Identify missing functional and non-functional requirements.
Check edge cases.
Review technical feasibility.
Evaluate whether the scope is realistic.
Suggest improvements.
Create an HLD, LLD, and Technical Requirement Document with a proper implementation plan.
These instructions define how the task should be performed.
2. Package
Instead of typing these instructions every time, we put them together into one organised unit.
For example:
PRD Review Skill
PRD Review Skill
│
├── Review problem statement
├── Check requirements
├── Check edge cases
├── Check technical feasibility
├── Evaluate scope
└── Provide recommendations
This entire collection of instructions becomes a skill.
3. Reusable
Now imagine that you have 30 student projects.
Without a Skill
You might repeatedly write:
"Review this PRD. Check the requirements, architecture, feasibility, scope, and edge cases..."
Then again:
"Review this PRD. Check the requirements, architecture, feasibility, scope, and edge cases..."
And again for every student.
This is repetitive and can also lead to inconsistent reviews.
With a Skill
You can simply say:
"Use my PRD Review Skill on this document."
The same set of instructions is then applied consistently to every project.
This makes the process:
Reusable
Consistent
Easier to maintain
Less repetitive
A Simple Real-World Analogy
Think of a dosa recipe.
A recipe for making dosa contains a sequence of instructions:
Mix rice + dal
↓
Soak
↓
Grind
↓
Ferment
↓
Cook
You don't reinvent these instructions every time you make dosa.
The recipe is reusable, but it is also specific to making dosa.
Similarly:
Skill = Recipe for an AI task
The skill tells the AI how to perform a particular task.
Examples of Skills
| Skill | What it teaches the AI |
|---|---|
| PRD Review | How to evaluate a PRD |
| Code Review | How to review code |
| Resume Review | How to evaluate a resume |
| Meeting Summary | How to turn a meeting transcript into structured notes |
| Research | How to conduct and present research |
| SQL Debugging | How to diagnose SQL problems |
Each skill contains the instructions and knowledge required to perform a specific type of task.
Skills in the Context of AI Agents
Skills become especially useful when building an AI agent.
Instead of putting every possible instruction directly into the agent, we can give the agent access to different skills.
AI Agent
│
├── PRD Review Skill
├── Code Review Skill
├── Research Skill
└── Documentation Skill
When the user asks:
"Review this PRD."
The agent can use the PRD Review Skill.
When the user asks:
"Review this code."
The agent can use the Code Review Skill.
This allows the agent to select the appropriate process depending on the task.
The Key Idea
The most important idea to remember is:
A skill separates "how to perform a task" from the AI itself.
The AI provides the general intelligence.
The skill provides the specific process, instructions, and context required for a particular task.
What Can a Skill Contain?
A skill can include:
Workflow — The steps that should be followed
Examples — Examples of good and bad outputs
Templates — Standard formats for producing output
Company policies and terminology — Organisation-specific rules and language
Reference documents — Documents that provide additional context
Optional scripts — Scripts that can help perform parts of the task
Prompt vs Skill vs Tool vs Plugin
It is important to understand the difference between these concepts.
| Concept | Simple Meaning | Example |
|---|---|---|
| Prompt | What you ask the AI right now | "Review this PRD." |
| Skill | A reusable how-to process for a particular job | "Here is how to review PRDs." |
| Tool | Something the AI can actually do or access | Search the web, query a database, create a Jira ticket |
| Plugin | A package that distributes capabilities such as skills, tools, or connectors | A packaged capability that can be installed |
A simple way to remember this is:
Prompt → What should I do?
Skill → How should I do it?
Tool → What can I use to do it?
Plugin → What packaged capabilities can I add?
Another Simple Analogy: An AI Chef
Imagine an AI as a chef.
Prompt
You tell the chef:
"Make me pasta."
That's the prompt.
It tells the chef what you want right now.
Skill
The chef has a standard pasta-making procedure:
Boil pasta
↓
Prepare sauce
↓
Add vegetables
↓
Mix
↓
Season
↓
Serve
That's the skill.
It defines how the chef should make pasta.
The same skill can be reused to make pasta for 10 different customers.
Tool
The chef needs equipment to actually perform the work:
Knife
Pan
Stove
Oven
Blender
These are the tools.
The skill says:
"Chop the vegetables."
The tool allows the chef to actually chop them.
So:
Skill → "Chop the vegetables."
Tool → Knife
Plugin
Now imagine a company sells a:
Professional Italian Cooking Kit
It contains:
Italian cooking recipes
+
Special cooking techniques
+
Specialised kitchen integrations
You install the whole package.
This is analogous to a plugin — a packaged capability that can provide multiple related capabilities to the AI.
Putting Everything Together
The concepts can be visualised like this:
USER
│
│ Prompt
▼
"Review this PRD"
│
▼
AI Agent
│
│ Selects
▼
PRD Review Skill
│
┌───────┼────────┐
▼ ▼ ▼
Workflow Rules Examples
│
▼
Tools
│
┌──────┼─────────┐
▼ ▼ ▼
Search Database Jira
The prompt tells the agent what the user wants.
The skill tells the agent how to perform that type of task.
The tools allow the agent to actually perform actions or access external information.
The plugin can package and distribute these capabilities.
In one line
Prompt = What to do Skill = How to do it Tool = What you can use to do it Plugin = A packaged set of capabilities
