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Agent Trajectory JSON Schema

A trajectory is a recording of one Agent run, used by the <agent-trajectory> Web Component to replay the ReAct loop step by step in the browser.

The schema mirrors the _emit(...) calls in chapter1/web-search-agent/agent.py so a real run can be exported into this format with almost no transformation.

Top-level object

{
  "$schema": "../SCHEMA.md",
  "experiment":  "ch1/web-search-agent",      // stable id, matches chapter/<exp>
  "title":       "GPT-5.6 解「东盟 10 国首都最近距离」",
  "model":       "gpt-5.6-sol",
  "task":        "东盟 10 国首都之间，最近的一对首都距离多少？",
  "condition":   "full-context",              // ablation condition, optional
  "outcome":     "success",                   // success | failure | loop | timeout
  "tags":        ["deep-research", "code-interp"],
  "recorded_at": "2026-07-20T14:32:08Z",
  "steps":       [ /* see below */ ]
}

Step types

Every step has iteration (1-based) and type. The remaining fields depend on type. The four types correspond exactly to ReAct: Reasoning / Acting / Observing / final Answer.

thought — model's internal reasoning

{
  "iteration": 1,
  "type":      "thought",
  "content":   "需要先找出东盟 10 国首都的名称，再查每对首都的距离……"
}

content comes from the model's reasoning_content field (Kimi K3, GPT-5 Reasoning, Claude thinking, …). May be long — the UI collapses it.

action — model called a tool

{
  "iteration": 1,
  "type":      "action",
  "tool":      "$web_search",
  "args":      { "query": "东盟 ASEAN 10 国首都 列表" }
}

tool is the tool name; args is the parsed argument object.

observation — tool returned a result

{
  "iteration": 1,
  "type":      "observation",
  "tool":      "$web_search",
  "content":   "东盟 10 国首都：雅加达、曼谷、吉隆坡、新加坡、马尼拉……"
}

For long results (search hits, code output), the UI shows a truncated view with a "show full" toggle.

answer — final user-facing answer

{
  "iteration": 3,
  "type":      "answer",
  "content":   "最近的一对首都是雅加达—吉隆坡，约 1184 km。"
}

Only one answer step per trajectory; it ends the replay.

Conventions

  • Iteration counter is the LLM call index (1-based), not the step index. A single iteration may emit thought + action + observation (3 steps).
  • No PII / no API keys. Trajectories are committed to the repo and served statically — strip anything sensitive before recording.
  • Keep it representative. Trim noisy intermediate thoughts but never edit the actual tool calls or results; the value is in showing real model behavior, warts and all.