Building custom tools in Agentic AI - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Tool Integration in Agentic AI

Which of the following best describes the primary purpose of building custom tools in an agentic AI system?

A To replace the AI's core reasoning engine with simpler rules

B To increase the AI's training dataset size automatically

C To reduce the AI model's size for faster inference

D To enable the AI to perform specific tasks by interacting with external systems or APIs

💡 Hint

Think about why an AI would need to connect to outside services or perform actions beyond just generating text.

Custom tools allow agentic AI to extend its capabilities by interacting with external APIs or systems, enabling it to perform tasks like fetching data, controlling devices, or executing commands.

❓ Predict Output

intermediate

Output of a Custom Tool Invocation

Given the following Python code snippet for a custom tool in an agentic AI framework, what will be the output when the tool is called with input '5'?

Agentic AI

def multiply_by_two(input_value):
    return f"Result: {int(input_value) * 2}"

output = multiply_by_two('5')
print(output)

A Result: 10

B Result: 25

C Result: 5

D TypeError

💡 Hint

Check how the input string is converted and multiplied.

The input '5' is converted to integer 5, then multiplied by 2, resulting in 10. The function returns the string 'Result: 10'.

❓ Hyperparameter

advanced

Choosing Timeout for External Tool Calls

When building a custom tool that calls an external API within an agentic AI system, which timeout setting is most appropriate to balance responsiveness and reliability?

A Set timeout to 0.1 seconds to ensure the AI never waits long

B Set timeout to 5 seconds to allow reasonable wait but avoid long delays

C Set timeout to 30 seconds to allow slow responses without blocking

D Do not set a timeout to wait indefinitely for the API response

💡 Hint

Consider user experience and network variability.

A 5-second timeout balances waiting long enough for typical API responses while preventing the AI from hanging too long, maintaining responsiveness.

❓ Metrics

advanced

Evaluating Custom Tool Effectiveness

Which metric is most suitable to evaluate the success of a custom tool integrated into an agentic AI that performs data retrieval tasks?

A Accuracy of the AI's language generation

B Latency of the tool's response time

C Precision and recall of the retrieved data matching user queries

D Number of parameters in the AI model

💡 Hint

Think about how well the tool returns relevant information.

Precision and recall measure how accurately and completely the tool retrieves relevant data, which is key for data retrieval tasks.

🔧 Debug

expert

Debugging a Custom Tool Integration Failure

Consider this Python code snippet for a custom tool in an agentic AI system that queries a weather API. The tool always returns 'None' instead of the expected temperature string. What is the most likely cause?

import requests

def get_temperature(city):
    response = requests.get(f"https://api.weather.com/temp?city={city}")
    if response.status_code == 200:
        data = response.json()
        return data['temperature']

print(get_temperature('London'))

A The API URL is incorrect or missing required parameters, causing no valid data returned

B The function does not convert the temperature to string before returning

C The requests library is not imported correctly

D The function should use POST instead of GET method

💡 Hint

Check if the API URL and parameters match the expected API specification.

If the API URL or parameters are wrong, the API may return a non-200 status or empty data, causing the function to return None.

Practice

1. What is the main purpose of building custom tools for an AI agent?

easy

A. To change the AI's language automatically

B. To add special skills that help the AI perform specific tasks

C. To reduce the size of the AI model

D. To make the AI run faster on any computer

Solution

1. Step 1: Understand what custom tools do

   Custom tools add new abilities or skills to an AI, making it better at certain jobs.

2. Step 2: Compare options to the purpose

   Only To add special skills that help the AI perform specific tasks talks about adding special skills, which matches the purpose of custom tools.

3. Final Answer:

   To add special skills that help the AI perform specific tasks -> Option B

4. Quick Check:

   Custom tools = add special skills [OK]

Hint: Custom tools add new skills to AI for tasks [OK]

Common Mistakes:

• Thinking custom tools speed up AI generally
• Confusing tool purpose with model size
• Assuming tools change AI language automatically

2. Which of the following is the correct way to define a custom tool in Python for an AI agent?

easy

A. tool = Tool(name='search', func=search_function)

B. tool = Tool('search', func=search_function)

C. tool = Tool(description='Find info', func=search_function)

D. tool = Tool(name='search', description='Find info', func=search_function)

Solution

1. Step 1: Recall required fields for a custom tool

   A custom tool needs a name, description, and a function to work properly.

2. Step 2: Check which option includes all three

   Only tool = Tool(name='search', description='Find info', func=search_function) has name, description, and func parameters correctly set.

3. Final Answer:

   tool = Tool(name='search', description='Find info', func=search_function) -> Option D

4. Quick Check:

   Tool needs name, description, and func [OK]

Hint: Include name, description, and func when defining tools [OK]

Common Mistakes:

• Omitting description or name
• Passing parameters in wrong order
• Using wrong parameter names

3. Given this Python code for a custom tool, what will be the output when calling tool.func('hello')?

def shout(text):
    return text.upper() + '!!!'
tool = Tool(name='shout', description='Make text loud', func=shout)

medium

A. 'HELLO!!!'

B. 'hello!!!'

C. 'hello'

D. Error: func is not callable

Solution

1. Step 1: Understand the function behavior

   The function shout converts text to uppercase and adds three exclamation marks.

2. Step 2: Apply the function to 'hello'

   Calling shout('hello') returns 'HELLO!!!'. Since tool.func points to shout, tool.func('hello') does the same.

3. Final Answer:

   'HELLO!!!' -> Option A

4. Quick Check:

   shout('hello') = 'HELLO!!!' [OK]

Hint: Check function logic and apply input to predict output [OK]

Common Mistakes:

• Ignoring uppercase conversion
• Missing exclamation marks
• Assuming func is not callable

4. You wrote this custom tool but get an error when using it. What is the likely problem?

def add_numbers(a, b):
    return a + b
tool = Tool(name='adder', description='Add two numbers', func=add_numbers)
result = tool.func(5)

medium

A. Tool name must be unique

B. Function add_numbers should not return a value

C. Missing one argument when calling tool.func

D. Description is too short

Solution

1. Step 1: Check function parameters

   add_numbers requires two inputs: a and b.

2. Step 2: Check how tool.func is called

   tool.func(5) provides only one argument, causing an error for missing the second argument.

3. Final Answer:

   Missing one argument when calling tool.func -> Option C

4. Quick Check:

   Function needs 2 args, only 1 given [OK]

Hint: Match function parameters with call arguments [OK]

Common Mistakes:

• Ignoring function argument count
• Thinking description length causes error
• Assuming tool name uniqueness causes runtime error

5. You want to build a custom tool that summarizes text by returning the first 10 words. Which code correctly defines this tool's function?

hard

A. def summarize(text):
return ' '.join(text.split()[:10])

B. def summarize(text):
return text[:10]

C. def summarize(text):
return text.split()[-10:]

D. def summarize(text):
return len(text.split())

Solution

1. Step 1: Understand the goal of the function

   The function should return the first 10 words, not characters or last words.

2. Step 2: Analyze each option

   def summarize(text): return ' '.join(text.split()[:10]) splits text into words and joins the first 10 words correctly. def summarize(text): return text[:10] returns first 10 characters, not words. def summarize(text): return text.split()[-10:] returns last 10 words. def summarize(text): return len(text.split()) returns word count, not summary.

3. Final Answer:

   def summarize(text): return ' '.join(text.split()[:10]) -> Option A

4. Quick Check:

   First 10 words = def summarize(text): return ' '.join(text.split()[:10]) [OK]

Hint: Split text and join first 10 words for summary [OK]

Common Mistakes:

• Returning characters instead of words
• Taking last words instead of first
• Returning word count instead of summary