AI Agents - lesson 1 | HackIndia Skills

AI Agents - lesson 1 | HackIndia Skills | HackIndia

Example

Tiny mental model

Imagine a campus event helper. A student asks, “What events are open today?” The model should not guess. It should call a tool that reads your events data.

The tool call is not the final answer. It is a request for your program to do work.

User: What events are open today?

Model returns a tool request:
{
  "tool": "list_open_events",
  "arguments": {
    "date": "2026-09-21"
  }
}

Your app runs list_open_events(date).

Tool result:
{
  "events": ["AI project clinic", "Web dev sprint"]
}

Model returns final answer:
Today you can join AI project clinic or Web dev sprint.

Example

First repo note

Before writing SDK code, add a small design note. This makes your project easier to review and keeps your agent scoped.

Use this as a starting file in your repo.

File: docs/agent-tools.md

Project: Campus Event Helper

User goal:
Find open college events and draft a registration message.

Tools the agent may call:
1. list_open_events
   Purpose: Read events available on a given date.
   Inputs: date
   Output: event names, timings, venue

2. get_event_details
   Purpose: Get rules and registration deadline for one event.
   Inputs: event_id
   Output: rules, fee, deadline

3. draft_registration_message
   Purpose: Draft a message the student can review before sending.
   Inputs: student_name, event_id
   Output: message text

Tools the agent must not call yet:
- send_message
- make_payment
- update_database

Why:
This first version can read and draft. It cannot take high-risk actions.

Tools make models act

The core idea

What counts as a tool

Tiny mental model

The basic loop

Common wrong idea

Name actions clearly

First repo note

Do this now

Quick check