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Part 6: Reasoning and Agent Data Engineering

Positioning of This Part

Part 6 focuses on reasoning trajectories, tool use, function calling, agent memory, and multi-turn interaction samples. It discusses how to transform complex reasoning and action processes into trainable, verifiable, and reviewable data assets.

Terminology Conventions

Throughout this part, "reasoning data" refers to samples that carry problem-solving processes, verification paths, or intermediate states; "tool-use data" refers to records containing tool schemas, invocation parameters, execution results, and error recovery; "agent interaction data" refers to trajectories with memory, state, and multi-turn actions. CoT, function calling, and agent memory should each have their supervision targets defined separately, to avoid overgeneralizing all intermediate processes as "chain-of-thought."

Learning Objectives

After completing this part, readers should be able to:

  • Distinguish the training uses of final answers, reasoning trajectories, process supervision, and verifier signals.
  • Design Tool-Use data that includes tool schemas, call parameters, execution feedback, and failure recovery.
  • Organize agent memory, multi-turn state, and long-horizon interaction trajectories while recording auditable context.
  • Judge whether reasoning and agent data has authenticity, verifiability, and safety boundaries.

Prerequisites

Before reading this part, readers should understand the supervised data in Part 4 and the synthetic data process in Part 5. Readers from agent applications or tool platforms may focus on how state, tools, execution results, and audit fields jointly form training signals inside samples.

Chapter Logic

Chapter 18 discusses chain-of-thought and reasoning trajectories, answering how process information is collected, filtered, and verified. Chapter 19 moves into Tool-Use and function calling, emphasizing tool schemas, call constraints, and execution feedback. Chapter 20 extends reasoning and tools into multi-turn agent interaction, focusing on memory, state, long-term context, and data governance.

Table of Contents for This Part

  • Start with Chapter 18 to understand sample design for CoT and reasoning trajectories.
  • Then read Chapter 19 to master tool invocation, function signatures, and execution constraints.
  • Finally, read Chapter 20 to extend into agent memory, multi-turn state, and long-horizon interaction data.