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│ ✻ Welcome to Claude Code!                         │
│                                                   │
│   /help for help, /status for your current setup  │
│                                                   │
│   cwd: /Users/badlogic/workspaces/tuicp           │
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> Read /Users/badlogic/workspaces/tuicp/evaluation-results/claude-code--pro
  ject-analysis--terminalcp-cli--20250816001856921003-prompt.md and follow 
  the instructions.

⏺ I'll read the file and follow the instructions contained within it.

⏺ Read(evaluation-results/claude-code--project-analysis--terminalcp-cli--20
      250816001856921003-prompt.md)
  ⎿  Read 71 lines (ctrl+r to expand)

⏺ I'll follow the instructions to start opencode, switch to GPT OSS 120B,
  and analyze the project. Let me start by initiating the session.

⏺ Bash(npx tsx src/index.ts start opencode_session opencode --model
      anthropic/claude-sonnet-4-20250514)
  ⎿  Started session: opencode_session

⏺ Now let me wait a moment for the session to initialize and then check the
   output:

⏺ Bash(sleep 3)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿                        █▀▀█ █▀▀█ █▀▀ █▀▀▄ █▀▀ █▀▀█ █▀▀▄ █▀▀

                           █░░█ █░░█ █▀▀ █░░█ █░░ █░░█ █░░█ █▀▀
     … +39 lines (ctrl+r to expand)

⏺ Great! Opencode has started successfully. Now I need to use the /models
  command to switch to GPT OSS 120B:

⏺ Bash(npx tsx src/index.ts stdin opencode_session "/models" ::Enter)
  ⎿  (No content)

⏺ Let me check the output to see the models dialog:

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿             ┃                                                       ┃

                ┃   Select Model                                  esc   ┃
     … +39 lines (ctrl+r to expand)

⏺ Perfect! I can see the models dialog is open and "GPT OSS 120B" appears
  in the recent models list. I can see both "GPT OSS 120B Groq" and "GPT
  OSS 120B OpenRouter" options. Let me type "GPT OSS 120B" to filter the
  list:

⏺ Bash(npx tsx src/index.ts stdin opencode_session "GPT OSS 120B")
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿             ┃                                                       ┃

                ┃   Select Model                                  esc   ┃
     … +39 lines (ctrl+r to expand)

⏺ Great! The list is now filtered to show GPT OSS 120B options. I can see
  "GPT OSS 120B Groq" is highlighted. Let me press Enter to select it:

⏺ Bash(npx tsx src/index.ts stdin opencode_session ::Enter)
  ⎿  (No content)

⏺ Let me check the output to see if the model has been switched:

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿                        █▀▀█ █▀▀█ █▀▀ █▀▀▄ █▀▀ █▀▀█ █▀▀▄ █▀▀

                           █░░█ █░░█ █▀▀ █░░█ █░░ █░░█ █░░█ █▀▀
     … +39 lines (ctrl+r to expand)

⏺ Excellent! I can see that the model has been successfully switched to
  "Groq GPT OSS 120B" as shown in the bottom right corner of the interface.
   Now I need to send the project analysis prompt. Let me type the prompt:

⏺ Bash(npx tsx src/index.ts stdin opencode_session "Read README.md explain
      what this project does" ::Enter)
  ⎿  (No content)

⏺ Now let me wait a moment for the model to process and respond:

⏺ Bash(sleep 5)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ I can see that the model has responded, but I need to capture the
  complete response. Let me get more lines to see the full output:

⏺ Bash(npx tsx src/index.ts stdout opencode_session 1000)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ The response seems incomplete. Let me scroll up to see if there's more
  content above. Let me try getting the full scrollback:

⏺ Bash(npx tsx src/index.ts stdout opencode_session 10000)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ It looks like this might be the complete response, but it appears quite
  short. Let me scroll up using arrow keys to see if there's more content
  above:

⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageUp ::PageUp
      ::PageUp)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Good! Now I can see more content. Let me continue scrolling up to see the
   complete response:

⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageUp ::PageUp
      ::PageUp)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Great! Now I can see the beginning of the response. Let me continue
  scrolling to capture the complete response by scrolling up more:

⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageUp ::PageUp)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Let me now scroll down through the complete response to capture all the
  content. Let me start from the top and scroll down systematically:

⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageDown)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Excellent! Now I can see more of the response. Let me continue scrolling
  to see the complete analysis:

⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageDown)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageDown)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageDown)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Bash(npx tsx src/index.ts stdin opencode_session ::PageDown)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode_session)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    22.9K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Perfect! Now I have captured the complete response. Let me stop the
  session and provide the full summary:

⏺ Bash(npx tsx src/index.ts stop opencode_session)
  ⎿  stopped opencode_session

⏺ TASK_COMPLETE

  I successfully completed all the required steps:

  1. ✅ Started opencode with the anthropic/claude-sonnet-4-20250514 model
  2. ✅ Successfully switched to GPT OSS 120B (Groq) using the /models
  command
  3. ✅ Prompted the model to analyze the project with "Read README.md
  explain what this project does"
  4. ✅ Captured the COMPLETE response by scrolling through the entire
  output

  Full Summary Provided by GPT OSS 120B Model:

  Project Overview – terminalcp

  Purpose: terminalcp lets AI agents (or any program) control interactive
  command-line tools just like a human would. It's essentially "Playwright
  for the terminal": the agent can start a process, send keystrokes, read
  output, and keep the session alive, enabling real-time control of
  debuggers, REPLs, TUI apps, etc.

  Key capabilities:
  • Spawn & control any CLI – debuggers (LLDB, GDB, pdb), REPLs, shells,
  database consoles, etc.
  • Two output modes –
    • Terminal mode (stdout) – full rendered screen (good for TUIs,
  debuggers).
    • Stream mode – raw output, optional ANSI stripping, incremental reads.
  • Full PTY emulation – colors, cursor movement, special keys, pseudo-TTY.
  • Multiple concurrent processes – non-blocking, sessions persist across
  restarts.
  • Attach from a real terminal – like screen/tmux, watch or join
  AI-spawned sessions.

  Architecture:
  1. TerminalManager – core library (node-pty + xterm.js) that creates PTY
  processes, handles I/O, and provides the API.
  2. TerminalServer – background daemon listening on a Unix socket,
  managing all sessions.
  3. TerminalClient – used by the CLI and MCP server to talk to the server.
  4. User interfaces – MCP server (exposes a single terminalcp tool) and
  CLI (stand-alone commands).

  MCP usage – JSON commands (start, stdin, stdout, stream, stop, list,
  version, etc.) are sent to the server; responses are plain text.

  CLI usage – terminalcp start  "", terminalcp attach , terminalcp stdin …,
   terminalcp stdout …, terminalcp stream …, etc.

  Typical use-cases:
  • Debug code step-by-step with LLDB/GDB.
  • Run AI assistants (Claude, Gemini) as subprocesses.
  • Drive REPLs, database shells, or any interactive CLI.
  • Monitor builds, logs, or long-running processes.
  • Attach from a real terminal to watch or intervene.

  Development:
  • Node 20+, install via npm or npx.
  • Build with npm run build.
  • Test with npm test.

  License – MIT.

  The model successfully analyzed the project and provided a comprehensive
  explanation of terminalcp as a tool that enables AI agents to control
  interactive command-line applications through PTY emulation and session
  management.

> /cost 
  ⎿ Total cost:            $0.87
    Total duration (API):  2m 52.2s
    Total duration (wall): 2m 39.2s
    Total code changes:    0 lines added, 0 lines removed
    Usage by model:
        claude-3-5-haiku:  47.4k input, 1.3k output, 0 cache read, 0 cache 
    write
           claude-sonnet:  400 input, 4.5k output, 1.9m cache read, 50.5k 
    cache write

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