CloudLLM RALPH Planner powered orchestration with Claude Sonnet 4.6 one shotting a Tetris Game in a single HTML File

tetris_planner_output.txt

MBP14inchDec2024:cloudllm gubatron$ cargo run --example tetris_planner_team
   Compiling cloudllm v0.10.6 (/Users/gubatron/workspace/cloudllm)
    Finished `dev` profile [unoptimized + debuginfo] target(s) in 1.35s
     Running `target/debug/examples/tetris_planner_team`

╔════════════════════════════════════════════════════════════════╗
║         TETRIS BUILDER — RALPH Orchestration Demo             ║
║               Claude Sonnet 4.6 Agent Team                     ║
╚════════════════════════════════════════════════════════════════╝

📐 ORCHESTRATION SETUP:
  Mode: RALPH (Iterative task-based coordination)
  Max Iterations: 8
  Agents: 4 specialists (researcher, architect, programmer, tester)
  Model: Claude Sonnet 4.6
  Shared Tools: Memory, file I/O

🎯 PROCESS:
  1. Agents read current HTML from Memory
  2. Each agent works on assigned task
  3. Agent writes updated HTML via write_tetris_file
  4. Mark [TASK_COMPLETE:task_id] when done
  5. Repeat until all 4 tasks complete

📊 TASKS:
  1. board_engine  — Board state, pieces (SRS), canvas shell
  2. gameplay_loop — Game loop, gravity, input, scoring, hold
  3. rendering_ui  — Draw board, ghost, next/hold panels, legend
  4. polish_audio  — Web Audio effects, mute toggle, start screen

═══════════════════════════════════════════════════════════════

🗑️  Cleared previous output: /Users/gubatron/workspace/cloudllm/tetris_planner_output.html
📄 Fresh game shell written at /Users/gubatron/workspace/cloudllm/tetris_planner_output.html (1010 bytes)

📋 Registering tool protocols...
  ├─ Memory protocol (GET/PUT/LIST for shared state)
  ├─ Custom protocol (read_file, write_tetris_file)
  └─ Done: 3 tools available

🔍 TOOL DESCRIPTIONS (exactly as agents will see them):
══════════════════════════════════════════════════════════════════════
[1] memory — Shared key-value store for agent coordination. Pass a 'command' string. Supported commands:
    Parameters:
      • command (string) [REQUIRED]
        Command string: 'G key', 'P key value [ttl]', 'L', 'D key', 'C'. Full-word aliases (GET/PUT/LIST/DELETE/CLEAR) also accepted.
      • key (string)
        Key for GET/PUT/DELETE when using split-parameter style instead of embedding the key in the command string.
      • value (string)
        Value for PUT when using split-parameter style. Must be a single token (no spaces). Use write_tetris_file for HTML content.
    Full description:
      
      READ a value:
      {"command": "G mykey"}                  — get key 'mykey'
      {"command": "GET", "key": "mykey"}  — same, split-param style
      
      WRITE a value (small values only; for large content use write_tetris_file):
      {"command": "P mykey myvalue"}                           — put without TTL
      {"command": "P", "key": "mykey", "value": "val"} — same, split-param style
      {"command": "P mykey myvalue 3600"}                      — put with 1-hour TTL
      
      LIST all keys:
      {"command": "L"}     — list keys
      {"command": "LIST"}  — same
      
      DELETE a key:
      {"command": "D mykey"}                   — delete key
      {"command": "DELETE", "key": "mykey"} — same
      
      CLEAR everything:
      {"command": "C"}  or  {"command": "CLEAR"}
      
      NOTE: PUT stores values as a single token — use write_tetris_file to persist HTML.

[2] write_tetris_file — Write the COMPLETE Tetris HTML/CSS/JS bundle to disk AND memory (CRITICAL: must include full document)
    Parameters:
      • path (string)
        Output path (defaults to tetris_planner_output.html if not specified)
      • content (string) [REQUIRED]
        Complete, valid HTML document including DOCTYPE, html, head (with style), body (with canvas and script)

[3] read_file — Read a UTF-8 text file from disk (returns content)
    Parameters:
      • path (string) [REQUIRED]
        Absolute or relative file path to read

══════════════════════════════════════════════════════════════════════

Starting RALPH orchestration with 4 agents and 4 PRD tasks...

[00:00] [orch] 🚀 Run started: RALPH Tetris Build [Ralph, 4 agents]
[00:00] [agent] 📝 Gameplay Researcher system prompt set
[00:00] [agent] 📝 Gameplay Programmer system prompt set
[00:00] [agent] 📝 QA & Polish system prompt set
[00:00] [agent] 📝 System Architect system prompt set
[00:00] [orch] 🔄 RALPH iteration 1/8 (0/4 tasks done)
[00:00] [orch] ── Round 1 ──
[00:00] [agent] ▶ Gameplay Researcher starting turn: === RALPH Iteration 1/8 ===

## Original Request
Build a fully playable Tetris game as a single HTML...
[00:00] [agent]   ├─ Gameplay Researcher LLM call #1 started
[01:39] [agent]   ├─ Gameplay Researcher LLM call #1 done (24736 chars, 11384 tokens)
[01:39] [agent] ✓ Gameplay Researcher completed (24736 chars, 11384 tokens, 0 tool calls)
[01:39] [orch]   Gameplay Researcher responded (24736 chars, 11384 tokens)
[01:39] [orch]   ✅ Gameplay Researcher completed: board_engine, gameplay_loop, rendering_ui, polish_audio → 4/4
[01:39] [agent] ▶ System Architect starting turn: === RALPH Iteration 1/8 ===

## Original Request
Build a fully playable Tetris game as a single HTML...
[01:39] [agent] 📨 System Architect received routed message
[01:39] [agent]   ├─ System Architect LLM call #1 started
[01:40] [agent]   ├─ System Architect LLM call #1 done (85 chars, 11420 tokens)
[01:40] [agent]   ├─ System Architect tool call #1: memory({"command":"G tetris_current_html"})
[01:40] [agent]   ├─ ✅ System Architect tool 'memory' succeeded [iter #1]
[01:40] [agent]   ├─ System Architect LLM call #2 started
[03:22] [agent]   ├─ System Architect LLM call #2 done (25075 chars, 32852 tokens)
[03:22] [agent] ✓ System Architect completed (25075 chars, 32852 tokens, 1 tool calls)
[03:22] [orch]   System Architect responded (25075 chars, 32852 tokens)
[03:22] [orch]   ✅ System Architect completed: board_engine, gameplay_loop, rendering_ui, polish_audio → 4/4
[03:22] [agent] 📨 Gameplay Programmer received routed message
[03:22] [agent] 📨 Gameplay Programmer received routed message
[03:22] [agent] ▶ Gameplay Programmer starting turn: === RALPH Iteration 1/8 ===

## Original Request
Build a fully playable Tetris game as a single HTML...
[03:22] [agent]   ├─ Gameplay Programmer LLM call #1 started
[05:00] [agent]   ├─ Gameplay Programmer LLM call #1 done (21574 chars, 29301 tokens)
[05:00] [agent] ✓ Gameplay Programmer completed (21574 chars, 29301 tokens, 0 tool calls)
[05:00] [orch]   Gameplay Programmer responded (21574 chars, 29301 tokens)
[05:00] [orch]   ✅ Gameplay Programmer completed: board_engine, gameplay_loop, rendering_ui, polish_audio → 4/4
[05:00] [agent] 📨 QA & Polish received routed message
[05:00] [agent] 📨 QA & Polish received routed message
[05:00] [agent] 📨 QA & Polish received routed message
[05:00] [agent] ▶ QA & Polish starting turn: === RALPH Iteration 1/8 ===

## Original Request
Build a fully playable Tetris game as a single HTML...
[05:00] [agent]   ├─ QA & Polish LLM call #1 started
[05:02] [agent]   ├─ QA & Polish LLM call #1 done (85 chars, 29344 tokens)
[05:02] [agent]   ├─ QA & Polish tool call #1: memory({"command":"G tetris_current_html"})
[05:02] [agent]   ├─ ✅ QA & Polish tool 'memory' succeeded [iter #1]
[05:02] [agent]   ├─ QA & Polish LLM call #2 started
[06:46] [agent]   ├─ QA & Polish LLM call #2 done (24604 chars, 68201 tokens)
[06:46] [agent] ✓ QA & Polish completed (24604 chars, 68201 tokens, 1 tool calls)
[06:46] [orch]   QA & Polish responded (24604 chars, 68201 tokens)
[06:46] [orch]   ✅ QA & Polish completed: board_engine, gameplay_loop, rendering_ui, polish_audio → 4/4
[06:46] [orch] ── Round 1 complete ──
[06:46] [orch] ✅ Run finished: 1 iterations, 141738 tokens, complete=true

╔════════════════════════════════════════════════════════════════╗
║                     RALPH RUN SUMMARY                         ║
╚════════════════════════════════════════════════════════════════╝

📊 RESULTS:
  Iterations Executed : 1
  Task Completion Rate : 100% (4.0/4 tasks)
  Total Tokens Used   : 141738
  Elapsed Time        : 6m 46s
  Status              : ✅ COMPLETE

📝 AGENT ACTIVITY:
  ✓ Gameplay Researcher (tetris-researcher)
  ✓ System Architect (tetris-architect)
  ✓ Gameplay Programmer (tetris-programmer)
  ✓ QA & Polish (tetris-playtester)

📋 DETAILED TURNS:
  [01] iter=1 agent=Gameplay Researcher  completed=board_engine,gameplay_loop,rendering_ui,polish_audio
  [02] iter=1 agent=System Architect     completed=board_engine,gameplay_loop,rendering_ui,polish_audio
  [03] iter=1 agent=Gameplay Programmer  completed=board_engine,gameplay_loop,rendering_ui,polish_audio
  [04] iter=1 agent=QA & Polish          completed=board_engine,gameplay_loop,rendering_ui,polish_audio

💾 FILE STATUS:
  ⚠️  write_tetris_file was NOT called — scanning response text for HTML...
  🔧 Extracted HTML from response text (rescue mode)
  856 lines, game_loop=true, pieces=true
  ✅ Written 23965 bytes to /Users/gubatron/workspace/cloudllm/tetris_planner_output.html

🎮 NEXT STEPS:
  ✅ Open /Users/gubatron/workspace/cloudllm/tetris_planner_output.html in a web browser
     (Rescued from response text — tool flow did not work as intended)