- banner:
  - navigation "Session hierarchy":
    - button "Use the ask_user_question tool to" [disabled]
  - tablist:
    - tab "Chat" [selected]
    - tab "Trajectory"
- text: "Use the ask_user_question tool to ask me exactly one multi-select question with id \"color\", question \"Which color do you prefer?\", header \"Pick one\", and two options: label \"Blue\" with description \"A cool recessive hue that reads as calm and trustworthy in long reading sessions and dense dashboards.\", and label \"Green\" with description \"A restful mid-spectrum hue with the highest perceived brightness, easiest on the eye over long sessions.\" Set multi_select to true. After I answer, reply with the single word DONE and stop. {{clock}}"
- button "Copy":
  - img
- button "Branch into a new conversation" [disabled]:
  - img
- text: Available only on the last message of a completed turn
- button "Context injection @deepseek-ai/dsh-system-prompt":
  - img
  - img
  - text: Context injection @deepseek-ai/dsh-system-prompt
- button "Think The user wants me to use the ask_user_question tool with specific parameters. Let me do exactly that.":
  - img
  - img
  - text: Think The user wants me to use the ask_user_question tool with specific parameters. Let me do exactly that.
- button "Ask question 1/1 answered":
  - img
  - img
  - text: Ask question 1/1 answered
- button "Think The user answered \"Blue\". I should now reply with the single word DONE and stop.":
  - img
  - img
  - text: Think The user answered "Blue". I should now reply with the single word DONE and stop.
- paragraph: DONE
- button "Copy":
  - img
- button "Branch into a new conversation":
  - img
- text: {{clock}} Ran for {{duration}} TTFT {{duration}} {{throughput}} tok/s
- textbox "Message the agent"
- button "Commands":
  - img
- 'button "Access mode, current: Workspace Write"': Workspace Write
- button "Select model, current DeepSeek-V4-Flash":
  - text: DeepSeek-V4-Flash
  - img
- button "3% of context used"
- button "Send message" [disabled]
- text: 1 turns · 2 steps LLM {{duration}} · Tool call {{duration}} TTFT avg {{duration}} · {{throughput}} tok/s Cache hit 95% Input 8.6K tok · Output 180 tok