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¶

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