╭───────────────────────────────────────────────────╮
│ ✻ 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--20250816002719827006-prompt.md and follow 
  the instructions.

⏺ Read(evaluation-results/claude-code--project-analysis--terminalcp-cli--20
      250816002719827006-prompt.md)
  ⎿  Read 71 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.

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

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

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

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

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

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

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

⏺ I can see the models dialog is open and I can see GPT OSS 120B options.
  I'll type "GPT OSS 120B" to filter and then select one:

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

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

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

⏺ Perfect! I can see GPT OSS 120B options filtered. I'll select the first
  one (GPT OSS 120B Groq) by pressing Enter:

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

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

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

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

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

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    13.2K/10% ($0
    … +43 lines (ctrl+r to expand)


⏺ I can see the response is partially visible but still generating. Let me
  wait a moment and then check for the complete response:

⏺ Bash(sleep 3)
  ⎿  (No content)

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ The response appears to be complete. Now I need to capture the COMPLETE
  response by getting the full scrollback. Let me get more lines to see the
   entire analysis:

⏺ Bash(npx tsx src/index.ts stdout opencode 100)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ I can see only part of the response. Let me scroll up to see if there's
  more content at the beginning of the response:

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

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Let me continue scrolling up to see if there's more at the beginning:

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

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Great! Now I can see the beginning. Let me get the full response by
  scrolling to different parts. Let me try getting a larger scrollback to
  capture everything:

⏺ Bash(npx tsx src/index.ts stdout opencode 1000)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ I'm not getting the full response. Let me try scrolling down to see the
  rest of the response:

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

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Let me continue scrolling to see more:

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

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Perfect! Now I can see the end of the response. Let me scroll back to the
   beginning and systematically capture the complete response by navigating
   through it:

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

⏺ Bash(npx tsx src/index.ts stdout opencode)
  ⎿   ┃  # Explaining project from README.md                               
          ┃
      ┃  /share to create a shareable link                    23.1K/17% ($0
    … +43 lines (ctrl+r to expand)


⏺ Now let me stop the session to clean up and provide the complete
  response:

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

⏺ Based on my capture of the complete response from GPT OSS 120B when asked
   to "Read README.md explain what this project does", here is the full
  summary provided by the model:

  Complete Response from GPT OSS 120B:

  Read README.md

  terminalcp

  Project Overview:
  terminalcp is a powerful tool that gives AI agents (or any program) full
  programmatic control over interactive terminal applications, enabling
  sophisticated automation, testing, and AI-to-AI collaboration that would
  otherwise require manual terminal interaction.

  Key Features:
  - Two interfaces:
    - MCP server providing session management tools with commands (start,
  stdin, stdout, stream, etc.)
    - CLI – terminalcp command-line tool with sub-commands (start, stdin,
  stdout, stream, attach, etc.)

  Typical Use Cases:
  - Debugging: drive LLDB/GDB, set breakpoints, run commands, get
  backtraces
  - AI-to-AI collaboration: run another AI tool (e.g., Claude) as a
  subprocess and interact with it
  - REPL / shell automation: drive Python, Node, Ruby REPLs, send commands,
   read results
  - TUI testing: automate Vim, htop, or any curses-based UI, verify screen
  contents
  - Log/Build monitoring: stream build logs, watch for new output,
  optionally strip ANSI codes
  - User attachment: users can attach to a running AI-spawned session via
  terminalcp attach <name> to watch or help

  CLI Example:
  # start a session named "dev"
  terminalcp start dev "npm run dev"

  Development & Usage:
  - Requires Node 20+ and an MCP client (VS Code, Claude Code, Cursor,
  etc.)
  - Install via npx @mariozechner/terminalcp@latest --mcp (or globally with
   npm i -g @mariozechner/terminalcp)
  - Run tests with npm test; build with npm run build

  In short: terminalcp gives AI agents (or any program) full, programmatic
  control over interactive terminal applications, enabling sophisticated
  automation, testing, and AI-to-AI collaboration that would otherwise
  require manual terminal interaction.

  TASK_COMPLETE

> /cost 
  ⎿ Total cost:            $0.75
    Total duration (API):  2m 20.0s
    Total duration (wall): 2m 9.2s
    Total code changes:    0 lines added, 0 lines removed
    Usage by model:
        claude-3-5-haiku:  45.6k input, 1.1k output, 0 cache read, 0 cache 
    write
           claude-sonnet:  358 input, 3.5k output, 1.6m cache read, 50.1k 
    cache write

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