ai-agent-book/chapter2/system-hint/CHANGELOG.md

System-Hint Agent Changelog

2026-07-18 - kimi-k3 (reasoning model) + offline status-bar preview

Changes Made

• Default model is now kimi-k3 (Moonshot's current flagship reasoning model), replacing the retired kimi-k2-*-preview line. provider="kimi"/"moonshot" both resolve to kimi-k3 unless --model overrides it.
• Reasoning-model handling: kimi-k3 returns a separate reasoning_content field alongside the final content. The agent reads the answer from content (FINAL ANSWER detection unchanged), calls with max_tokens=8192 (well above the reasoning minimum of 2048), and forces temperature=1 for reasoning models via _reasoning_safe_temperature() (kimi-k3 / gpt-5). Assistant turns are replayed with model_dump() (which includes reasoning_content); the Moonshot API accepts this on follow-up calls, so multi-turn tool loops work unchanged.
• Offline status-bar preview (python main.py --mode preview): renders all five status-bar techniques as before/after comparisons with no API key and no LLM call. Honors --no-timestamps / --no-counter / --no-todo / --no-errors / --no-state to isolate individual techniques.

2025-09-30 - Trajectory Logging Enhancement

Changes Made

1. Full LLM Messages in Trajectory

Added tracking of the complete messages list sent to the LLM, including system hints:

• Added field: last_llm_messages to SystemHintAgent class

  • Stores the full messages array sent to the LLM, including the system hint appended as a user message
  • This differs from conversation_history which only stores the base conversation without the dynamic system hints

• Modified methods:

  • __init__: Initialize last_llm_messages = None
  • execute_task: Capture messages_to_send before LLM call and store as self.last_llm_messages
  • _save_trajectory: Include last_llm_messages in the trajectory JSON output
  • reset: Reset last_llm_messages to None

2. Real System Time (No Mock Time)

Verified and ensured real system time is used throughout:

• Default configuration: simulate_time_delay = False (line 68 in agent.py)

  • When False, uses datetime.now() for all timestamps
  • When True (only for demos), uses simulated time

• Timestamp sources:

  • _get_timestamp(): Uses datetime.now() when simulate_time_delay=False
  • trajectory_data['timestamp']: Always uses datetime.now().isoformat()
  • Tool call timestamps: Always use datetime.now().isoformat()
  • TODO item timestamps: Always use datetime.now().isoformat()

Benefits

1. Complete LLM Context: The last_llm_messages field in trajectory.json now shows exactly what was sent to the LLM, including dynamic system hints about current state, TODO list, timestamps, etc.

2. Debugging: Easier to debug agent behavior by seeing the complete context the LLM received, not just the conversation history

3. Accurate Timestamps: All timestamps reflect real system time for accurate trajectory analysis and debugging

Example Trajectory Structure

{
  "timestamp": "2025-09-30T20:26:32.057323",
  "iteration": 1,
  "provider": "kimi",
  "model": "kimi-k3",
  "conversation_history": [
    {"role": "system", "content": "..."},
    {"role": "user", "content": "[2025-09-30 20:26:00] Task..."},
    {"role": "assistant", "content": "..."}
  ],
  "last_llm_messages": [
    {"role": "system", "content": "..."},
    {"role": "user", "content": "[2025-09-30 20:26:00] Task..."},
    {"role": "assistant", "content": "..."},
    {"role": "user", "content": "=== SYSTEM STATE ===\nCurrent Time: 2025-09-30 20:26:32\n..."}
  ],
  "tool_calls": [...],
  "todo_list": [...],
  "current_directory": "/path/to/dir",
  "final_answer": null,
  "config": {
    "enable_timestamps": true,
    "enable_tool_counter": true,
    "enable_todo_list": true,
    "enable_detailed_errors": true,
    "enable_system_state": true,
    "timestamp_format": "%Y-%m-%d %H:%M:%S",
    "simulate_time_delay": false
  }
}

Differences: conversation_history vs last_llm_messages

• conversation_history: Permanent record of the conversation between user and assistant

  • System prompt
  • User messages (with timestamps if enabled)
  • Assistant responses
  • Tool call messages and results

• last_llm_messages: Complete snapshot of what was sent to LLM in the last call

  • Everything from conversation_history
  • PLUS: Dynamic system hint appended as final user message
  • Shows current system state, TODO list, directory, time
  • This is what the LLM actually sees when making decisions

Testing

All changes have been tested and verified:

• ✅ last_llm_messages correctly captured and saved
• ✅ Real system timestamps used (not simulated time)
• ✅ Trajectory JSON format validated
• ✅ No linter errors
• ✅ Backward compatible with existing code