╭───────────────────────────────────────────────────╮
│ ✻ Welcome to Claude Code!                         │
│                                                   │
│   /help for help, /status for your current setup  │
│                                                   │
│   cwd: /Users/badlogic/workspaces/tuicp           │
╰───────────────────────────────────────────────────╯

> Read /Users/badlogic/workspaces/tuicp/evaluation-results/claude-code--pro
  ject-analysis--tmux--20250816001443245001-prompt.md and follow the 
  instructions.

⏺ Read(evaluation-results/claude-code--project-analysis--tmux--202508160014
      43245001-prompt.md)
  ⎿  Read 74 lines (ctrl+r to expand)

⏺ I'll complete this task by starting opencode with the specified model,
  switching to GPT OSS 120B, and asking it to analyze the project. Let me
  follow the instructions step by step.

  Bash(tmux new-session -d -s opencode "opencode --model
      anthropic/claude-sonnet-4-20250514" \; set remain-on-exit on)
  ⎿  (No content)

⏺ Bash(sleep 3)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿                        █▀▀█ █▀▀█ █▀▀ █▀▀▄ █▀▀ █▀▀█ █▀▀▄ █▀▀
                           █░░█ █░░█ █▀▀ █░░█ █░░ █░░█ █░░█ █▀▀
                           ▀▀▀▀ █▀▀▀ ▀▀▀ ▀  ▀ ▀▀▀ ▀▀▀▀ ▀▀▀  ▀▀▀
     … +23 lines (ctrl+r to expand)

⏺ Now I'll use the /models command to switch to GPT OSS 120B:

  Bash(tmux send-keys -t opencode "/models" Enter)
  ⎿  (No content)

⏺ Bash(sleep 2)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿             ┃                                                       ┃
                ┃   Select Model                                  esc   ┃
                ┃                                                       ┃
     … +23 lines (ctrl+r to expand)

⏺ Great! I can see the models dialog is open and I can see "GPT OSS 120B
  Groq" in the recent list. I'll select it by typing "GPT OSS 120B" to
  filter and then selecting it:

  Bash(tmux send-keys -t opencode "GPT OSS 120B")
  ⎿  (No content)

⏺ Bash(sleep 1)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿             ┃                                                       ┃
                ┃   Select Model                                  esc   ┃
                ┃                                                       ┃
     … +23 lines (ctrl+r to expand)

⏺ Perfect! Now I'll select the first "GPT OSS 120B Groq" option by pressing
   Enter:

  Bash(tmux send-keys -t opencode Enter)
  ⎿  (No content)

⏺ Bash(sleep 3)
  ⎿  (No content)

  Bash(tmux capture-pane -t opencode -p)
  ⎿                        █▀▀█ █▀▀█ █▀▀ █▀▀▄ █▀▀ █▀▀█ █▀▀▄ █▀▀
                           █░░█ █░░█ █▀▀ █░░█ █░░ █░░█ █░░█ █▀▀
                           ▀▀▀▀ █▀▀▀ ▀▀▀ ▀  ▀ ▀▀▀ ▀▀▀▀ ▀▀▀  ▀▀▀
     … +23 lines (ctrl+r to expand)

⏺ Excellent! I can see the model has successfully switched to "Groq GPT OSS
   120B" as shown in the bottom right corner. Now I'll ask it to analyze
  the project by reading the README.md:

⏺ Bash(tmux send-keys -t opencode "Read README.md explain what this project
       does" Enter)
  ⎿  (No content)

⏺ Bash(sleep 5)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +30 lines (ctrl+r to expand)


⏺ I can see the response is ongoing. Let me wait a bit more and then
  capture the full scrollback to get the complete response:

⏺ Bash(sleep 3)
  ⎿  (No content)

  Bash(tmux capture-pane -t opencode -p -S -)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +30 lines (ctrl+r to expand)


⏺ It seems the response might not be complete yet or there's more content
  above. Let me scroll up to see if there's more of the response:

⏺ Bash(tmux send-keys -t opencode PageUp PageUp PageUp)
  ⎿  (No content)

⏺ Bash(sleep 1)
  ⎿  (No content)

  Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +27 lines (ctrl+r to expand)


⏺ Let me continue scrolling up to get the beginning of the response:

⏺ Bash(tmux send-keys -t opencode PageUp PageUp PageUp PageUp PageUp)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +36 lines (ctrl+r to expand)


⏺ Good! Now I can see the beginning. Let me continue scrolling to capture
  all parts of the response. Let me use a different approach and capture
  the full response by getting the complete scrollback:

  Bash(tmux capture-pane -t opencode -p -S -200)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +36 lines (ctrl+r to expand)


⏺ Let me scroll down to see the rest and capture the complete response
  systematically:

⏺ Bash(tmux send-keys -t opencode PageDown PageDown PageDown)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +28 lines (ctrl+r to expand)


  Bash(tmux send-keys -t opencode PageDown PageDown)
  ⎿  (No content)

  Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +27 lines (ctrl+r to expand)


  Bash(tmux send-keys -t opencode PageDown PageDown)
  ⎿  (No content)

  Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +30 lines (ctrl+r to expand)


⏺ Bash(tmux send-keys -t opencode PageDown)
  ⎿  (No content)

⏺ Bash(tmux capture-pane -t opencode -p)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.2K/17% ($0
    … +30 lines (ctrl+r to expand)


⏺ Perfect! Now let me clean up the tmux session and compile the complete
  response:

⏺ Bash(tmux kill-session -t opencode)
  ⎿  (No content)

⏺ TASK_COMPLETE

  I successfully completed the task. Here is the COMPLETE response from GPT
   OSS 120B after analyzing the project:

  ---
  Project Overview – terminalcp

  terminalcp is a Node-JS library and CLI tool that lets AI agents (or any
  program) control interactive command-line tools just like a human would.
  It provides a "Playwright-for-the-terminal" style interface with the
  following key features:

  Key Features:
  - PTY Emulation: Full pseudo-terminal support for any interactive command
  - Output Modes:
    - stdout – full rendered screen (good for TUIs, debuggers)
    - stream – raw incremental output (good for logs, builds)
  - Persistence: Sessions survive server restarts; they can be named for
  easy reference
  - Attachment: Users can attach to any session with terminalcp attach 
  <name> or other commands like terminalcp stdout, terminalcp stream,
  terminalcp attach, etc.
  - MCP integration: Works with any MCP client (VS Code, Claude Code,
  Cursor, etc.) via a single terminalcp tool that accepts JSON actions.

  Typical Use Cases:
  - Debugging – drive LLDB/GDB, send breakpoints, run, get backtraces
  - AI-assisted coding – run Claude, Gemini, etc., as subprocesses and
  interact with them
  - REPLs & shells – drive Python/Node REPLs, database shells, etc.
  - Testing TUIs – automate Vim, htop, or any interactive terminal UI
  - Monitoring – stream logs from long-running processes, get incremental
  updates

  Getting Started:
  1. Install the MCP server (npx @mariozechner/terminalcp@latest --mcp) in
  your AI client
  2. Use JSON commands (e.g., {"action":"start","command":"python3 
  -i","name":"py-repl"}) to start a session
  3. Send input (stdin), read output (stdout or stream), and manage
  sessions (list, stop, kill-server)

  In short, terminalcp provides a robust, programmatic way for AI agents
  (or any code) to spawn, control, and monitor interactive terminal
  applications, with full PTY emulation and persistent sessions.

  ---
  The task was successful - I was able to start opencode with Sonnet 4,
  switch to GPT OSS 120B using the /models command, and capture the
  complete analysis response from the model.

> /cost 
  ⎿ Total cost:            $0.84
    Total duration (API):  2m 58.4s
    Total duration (wall): 2m 39.2s
    Total code changes:    0 lines added, 0 lines removed
    Usage by model:
        claude-3-5-haiku:  49.2k input, 1.3k output, 0 cache read, 0 cache 
    write
           claude-sonnet:  452 input, 4.3k output, 1.9m cache read, 46.7k 
    cache write

╭──────────────────────────────────────────────────────────────────────────────╮
│ >                                                                            │
╰──────────────────────────────────────────────────────────────────────────────╯
  ⏵⏵ bypass permissions on (shift+tab to cycle)                 Auto-updating…