Autonomous Task Planning Agent

Objectives

• Use create_react_agent to build a ReAct Agent with at least 4 tools (search, calculation, file read/write, task logging), and verify the complete Thought→Action→Observation loop output using verbose mode
• Implement a Plan-and-Execute pattern-based task planner that can automatically decompose a complex goal (e.g., 'research a domain and generate a report') into 3 or more ordered subtasks and execute them sequentially
• Add a task state management mechanism to the Agent that tracks the execution status of each subtask (pending / in-progress / completed / failed), and outputs a structured execution summary upon task completion
• Handle exceptions during Agent execution: configure handle_parsing_errors and max_iterations to ensure the Agent can gracefully degrade and return partial results when a tool call fails or reasoning enters an infinite loop

Hints

• ReAct prompt templates are extremely sensitive to tool descriptions — if the Agent frequently selects the wrong tool, first check whether your tool descriptions are clear and unambiguous; consider adding usage examples to illustrate when each tool should be used
• The Planner in Plan-and-Execute is essentially a single LLM call — you can inject constraints via the System Prompt (e.g., 'each plan step must be independently verifiable') to improve plan quality
• When the Agent gets stuck in a repetitive 'Thought→Action→Thought→Action' loop, it's usually because the Observation returned by the tool lacks sufficient information — try having tools return more contextual information, or explicitly include 'the next step should be...' in the Observation
• Task state management can be implemented with a simple Python dict or SQLite database, wrapped as a special 'state query tool' that allows the Agent to read and write task states on its own
• When testing the Agent, it is recommended to start with simple single-step tasks and gradually increase complexity — first verify that individual tool calls work correctly, then test multi-tool collaboration, and finally test the complete plan-and-execute workflow

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