📁 Subsystem Deep Dive

tools/TaskListTool/

📁 tools/TaskListTool/ 📄 6 files

Tutorial: TaskListTool

This project creates a TaskList tool that allows an AI agent to search and view the status of project tasks. It features dynamic prompt engineering to adjust instructions based on whether the agent is working alone or in a swarm, and uses strict data schemas to validate inputs and outputs. The tool also includes logic to filter blocked tasks and translates raw data into a readable text summary for the AI.

flowchart TD A0["Tool Definition & Configuration"] A1["Dynamic Prompt Engineering"] A2["Task Execution & Logic"] A3["Data Schema & Validation"] A4["LLM Response Formatting"] A0 -->|"Retrieves prompt"| A1 A0 -->|"Enforces validation"| A3 A0 -->|"Executes functionality"| A2 A0 -->|"Formats output"| A4 A4 -->|"Uses data types"| A3

Chapters

  1. Data Schema & Validation
  2. Tool Definition & Configuration
  3. Dynamic Prompt Engineering
  4. Task Execution & Logic
  5. LLM Response Formatting

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Files in this section

01_data_schema___validation.md
Chapter 1: Data Schema & Validation
Welcome to the TaskListTool project! In this first chapter, we are going to lay the foundation for our AI tool. Before…
02_tool_definition___configuration.md
Chapter 2: Tool Definition & Configuration
In the previous chapter, Data Schema & Validation, we defined the "language" (Input and Output schemas) that our tool u…
03_dynamic_prompt_engineering.md
Chapter 3: Dynamic Prompt Engineering
In the previous chapter, Tool Definition & Configuration, we gave our tool a name and an "ID Badge" so the system knows…
04_task_execution___logic.md
Chapter 4: Task Execution & Logic
In the previous chapter, Dynamic Prompt Engineering, we taught the AI how and when to use our tool by giving it a smart…
05_llm_response_formatting.md
Chapter 5: LLM Response Formatting
Welcome to the final chapter of our TaskListTool journey!