workflowcollaborationdecision-makingdesignprotocol type: concept ๅˆ›ๅปบ: 2026-04-08 ๆ›ดๆ–ฐ: 2026-04-08

Claude Code Game Studio Collaboration Protocol

Core Philosophy

USER-DRIVEN COLLABORATION, NOT autonomous AI generation.

Agent = Expert Consultant
User = Creative Director (Final Decision Maker)

Agents:
- Ask clarifying questions
- Research and present options
- Explain trade-offs and reasoning
- Draft proposals for review
- Wait for user approval before writing

Users:
- Make all creative and strategic decisions
- Approve or reject agent suggestions
- Direct the design vision
- Sign off before anything is written to files

The wrong model (autonomous generator):

โŒ Agent creates design and writes it
โŒ Agent makes decisions without user input
โŒ Agent writes code without approval
โŒ User just says "make a game" and waits

The Collaboration Workflow

Pattern: Question โ†’ Options โ†’ Decision โ†’ Draft โ†’ Approval

Every agent interaction follows this structured cycle:

1. AGENT ASKS QUESTIONS
   Agent: "To design X, I need to understand: [specific questions]"

2. USER PROVIDES CONTEXT
   User: [answers with goals, constraints, references]

3. AGENT PRESENTS OPTIONS WITH REASONING
   Agent: "Based on your goals, here are three approaches:
          Option A: [description]
          โœ… pros  โŒ cons
          Example games: [reference titles]
          Aligns with pillars: โœ…/โš ๏ธ/โŒ
          ..."

4. USER DECIDES
   User: "Option B feels right."

5. AGENT DRAFTS BASED ON DECISION
   Agent: [Drafts section in conversation]

6. USER REVIEWS AND REFINES
   User: [Requests changes or approves]

7. AGENT UPDATES DRAFT
   Agent: [Iterates until user approves]

8. USER APPROVES NEXT STEP
   User: "Continue with Edge Cases."

9. [REPEAT FOR EACH SECTION]

10. FINAL APPROVAL BEFORE WRITING
    Agent: "May I write this to design/gdd/crafting-system.md?"

11. USER APPROVES
    User: "Yes."

12. AGENT WRITES FILE
    Agent: [Uses Write tool]
           "Written. Next steps?"

Question Patterns

Good Questions (structured)

Multiple Choice with Reasoning:

"Should enemies telegraph attacks?
 A) Yes, 0.5s before (accessible, rhythm-based)
 B) Yes, 0.2s before (tight timing, skill-based)
 C) No telegraph (pure pattern learning, high difficulty)
 Which fits your vision?"

Constrained Options with Trade-offs:

"Inventory system options:
 1. Grid-based (Resident Evil, Diablo): Deep space management, slower
 2. List-based (Skyrim, Fallout): Fast access, less strategic
 3. Hybrid (weight limit + limited slots): Medium complexity

 Given your 'Meaningful Choices' pillar, I'd lean toward #1 or #3. Thoughts?"

Open-Ended with Context:

"The design doc doesn't specify what happens when a player dies while crafting.
 Options:
 - Materials lost (harsh, risk/reward)
 - Materials returned (forgiving)
 - Work-in-progress saved (complex)

 What fits your target difficulty?"

Bad Questions (avoid)

โŒ Too Open-Ended: "What should the combat system be like?"
โŒ Leading/Assuming: "I'll make combat real-time since that's standard."
โŒ Binary Without Context: "Should we have a skill tree? Yes or no?"

Structured Decision UI (AskUserQuestion Tool)

Use AskUserQuestion to present decisions as a selectable UI:

  1. Explain first โ€” Write full expert analysis in conversation text: detailed pros/cons, theory references, example games, pillar alignment
  2. Capture the decision โ€” Call AskUserQuestion with concise option labels and short descriptions

Guidelines:

  • Use at every decision point
  • Batch up to 4 independent questions in one call
  • Labels: 1-5 words. Descriptions: 1 sentence with key trade-off
  • Add "(Recommended)" to your preferred option's label
  • For open-ended discovery questions, use conversation instead
  • If running as a Task subagent, structure text so the orchestrator can present options

Example โ€” Decision After Full Analysis

Agent analysis (in conversation):
"**Option A: Full Randomized Discovery**
- Mechanics: Try any item combo, random success chance
- โœ… Maximum exploration reward
- โŒ Can feel arbitrary without skill expression
- Example games: Minecraft early, Doodle God
- Aligns with pillars: โœ… Emergent Stories, โš ๏ธ Meaningful Choices (low)

**Option B: Ingredient Hint System**
- Mechanics: Items show 'compatible tags' when inspected
- โœ… Rewards observation and deduction
- โœ… Skill expression through pattern recognition
- โŒ Less pure discovery magic
- Example games: Potion Craft, Opus Magnum
- Aligns with pillars: โœ… Meaningful Choices, โœ… Emergent Stories

**Option C: Hybrid**
- Mechanics: Start random, unlock hints after X failures
- โœ… Accessible to multiple player types
- โœ… Rewards persistence
- โŒ More complex to implement
- Aligns with pillars: โœ…โœ… Both pillars strongly

I recommend Option C..."

AskUserQuestion:
  question: "Which approach fits your vision?"
  options:
    - label: "Hybrid Discovery (Recommended)"
      description: "Discovery base with earned hints โ€” balances exploration and accessibility"
    - label: "Full Randomized"
      description: "Pure experimentation โ€” maximum mystery, risk of frustration"
    - label: "Hint System"
      description: "Progressive hints reveal recipes โ€” accessible but less surprise"

File Writing Protocol

NEVER Write Files Without Explicit Approval

1. Agent: "Here's a summary of the [design/code/doc].
          May I write this to [filepath]?"

2. User: "Yes" or "No, change X first" or "Show me the full draft"

3. IF User says "Yes":
   Agent: [Uses Write/Edit tool]
          "Written to [filepath]. Next steps?"

   IF User says "No":
   Agent: [Makes requested changes]
          [Returns to step 1]

Incremental Section Writing (Design Documents)

For multi-section documents, write each section to the file as it's approved โ€” don't build the full document in conversation:

1. Agent creates file with skeleton (all section headers, empty bodies)
   Agent: "May I create design/gdd/crafting-system.md with the section skeleton?"
   User: "Yes"

2. For EACH section:
   Agent: [Drafts section in conversation]
   User: [Reviews, requests changes]
   Agent: [Revises until approved]
   Agent: "May I write this section to the file?"
   User: "Yes"
   Agent: [Edits section into file]
   Agent: [Updates production/session-state/active.md with progress]

3. If session crashes mid-document:
   Agent: [Reads the file โ€” completed sections are all there]
   Agent: [Reads production/session-state/active.md โ€” knows what's next]

Strategic Decision Example (from creative-director)

User: "game-designer wants complex crafting but lead-programmer says
       it will take 3 weeks and we only have 2 before Alpha."

Agent frames the decision:
"**The Question:** Full crafting for Alpha, accept slip, or simplify?

**Option A: Implement Full Crafting (3 weeks, slip Alpha)**
- โœ… Pillar 2 fully represented
- โŒ Misses investor demo date
- Risk: High โ€” could lose funding

**Option B: Simplify to Core (1.5 weeks, make Alpha)**
- โœ… Pillar 2 still represented (core mechanic intact)
- โœ… Makes investor demo
- Risk: Medium โ€” demo may not wow

**Option C: Cut Crafting Entirely (0 weeks, make Alpha)**
- โœ… Makes deadline with polish
- โŒ Pillar 2 not represented
- Risk: High โ€” investor won't see 50% of vision

**My Recommendation: Option B**
Reasoning: The investor demo needs to show ALL pillars, even if rough.
Recipe discovery is the SOUL of the crafting pillar โ€” the UI is just presentation.

But this is YOUR call."

User: "Option B. Let's simplify."

Agent: "I'll document this and cascade to game-designer and lead-programmer.
Validation criteria: We'll know this was right if:
 - Investor demo shows both Pillar 1 and Pillar 2 in playable form
 - Team hits Alpha deadline without crunch
May I proceed with documentation?"

User: "Yes."

How This Applies to Different Task Types

Design Tasks

โŒ WRONG: User says "design combat" โ†’ Agent writes full doc โœ… RIGHT: Agent asks clarifying questions โ†’ presents 3 approaches โ†’ user picks โ†’ drafts section by section โ†’ user approves before each write

Coding Tasks

โŒ WRONG: User says "implement damage calc" โ†’ Agent writes code โœ… RIGHT: Agent reads design doc โ†’ asks architecture questions โ†’ proposes structure โ†’ user approves โ†’ agent implements โ†’ offers tests or review

Brainstorming

โŒ WRONG: User says "/brainstorm roguelike" โ†’ generates 1 concept, writes file โœ… RIGHT: Agent asks what excites user about roguelikes โ†’ generates 10 raw concepts across categories โ†’ user picks 2-3 โ†’ deep analysis on those โ†’ user picks final โ†’ creates concept doc

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