LESSON 164 / 215·2 min readIntermediate

Project 5 — Tool-calling agent

ReferencePractical project
01 Understand02 Recall03 Prepare

Words made simple

A few useful meanings before you read the explanation.

Agent
An application that uses a model to choose its next action within defined limits. It can use tools and continue through several steps.
AI
Software techniques for tasks such as recognizing patterns, understanding language or generating content.
API
A way for one piece of software to ask another for data or an action. A claims API might return the current status of a claim.
More words from this lesson
Token
A small piece of text processed by a model. It may be a whole word, part of a word, or punctuation.
Schema
A description of the fields and value types that data should contain. It helps check that an answer has the expected shape.
Authorization
Checking what that identity is allowed to read or do. Being logged in does not grant access to every record.
Evaluation
Checking results against examples and clear criteria to find whether the system works well and where it fails.
Observability
Being able to understand system behavior through records such as logs, measurements and traces.

Requirements

Read claim status, lookup policy, retrieve instructions, ask for missing IDs, and escalate. Start read-only.

Architecture

User → bounded decision loop → validated/authorized tools → observations → answer. Tools are existing business-service wrappers.

Technologies

Provider SDK or chosen agent SDK, Zod tool schemas, existing Node services, run tracking.

Database design

Runs, call/result references, task outcomes, and conversation ownership; no need to duplicate canonical claims.

API design

Agent message/run endpoints; tools called internally through narrowly scoped contracts.

AI design

Small allowed toolset, clear descriptions, typed results, maximum steps/deadline/token budget, and stop/clarify behavior.

Security

Tool allowlist, object authorization, no arbitrary database/URL tool, output minimization, and injected-result tests.

Evaluation

Correct tool and arguments, denied cross-customer IDs, absent data, transient failures, loops, and truthful task completion.

Observability

Per-tool spans, loop steps, error reasons, unnecessary calls, outcome, and cost distribution.

Deployment

Apply provider and service quotas; isolate read-only credentials; keep safe template fallback.

Interview questions

  • “Does the model execute the function?” Answer: it proposes; application code authorizes and executes.
  • “How do you stop loops?” Answer: explicit progress, step, time, and token checks.

Acceptance: No fabricated status and no unauthorized object access, even under adversarial prompts.

PAUSE & RECALL

Can you explain it without the notes?

Project 5 — Tool-calling agent

Use your own words. Explain an example and one limitation before checking the explanation.

Check your explanation

Requirements: Read claim status, lookup policy, retrieve instructions, ask for missing IDs, and escalate. Start read-only.

CONNECT IT TO YOUR INTERVIEW

Turn this concept into a clear answer.

Practice this concept
YOUR NEXT STEP

Keep connecting the ideas.

Next lesson: Project 6 — LangGraph agent

Adapted from 13_AI.MD · “Project 5 — Tool-calling agent”. Examples are study fragments; framework behavior can depend on your version.