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Donchitos ad540fe75d Game Studio Agent Architecture — complete setup (Phases 1-7)

48 coordinated Claude Code subagents for indie game development:
- 3 leadership agents (creative-director, technical-director, producer)
- 10 department leads (game-designer, lead-programmer, art-director, etc.)
- 23 specialist agents (gameplay, engine, AI, networking, UI, tools, etc.)
- 12 engine-specific agents (Godot, Unity, Unreal with sub-specialists)

Infrastructure:
- 34 skills (slash commands) for workflows, reviews, and team orchestration
- 8 hooks for commit validation, asset checks, session management
- 11 path-scoped rules enforcing domain-specific standards
- 28 templates for design docs, reports, and collaborative protocols

Key features:
- User-driven collaboration protocol (Question → Options → Decision → Draft → Approval)
- Engine version awareness with knowledge-gap detection (Godot 4.6 pinned)
- Phase gate system for development milestone validation
- CLAUDE.md kept under 80 lines with extracted doc imports

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-02-13 21:04:24 +11:00

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Context Management

Context is the most critical resource in a Claude Code session. Manage it actively:

Compact proactively at ~65-70% context usage, not reactively when at the limit
Use /clear between unrelated tasks, or after 2+ failed correction attempts
Context budgets by task type:
- Light (read/review): ~3k tokens startup
- Medium (implement feature): ~8k tokens
- Heavy (multi-system refactor): ~15k tokens
Preserve during compaction: modified file list, active sprint tasks, architectural decisions made this session, agent invocation outcomes, test results, unresolved blockers
When delegating to subagents, provide full context in the prompt -- subagents do not inherit conversation history unless explicitly given it

Compaction Instructions

When context is compacted, preserve the following in the summary:

List of files modified in this session and their purpose
Any architectural decisions made and their rationale
Active sprint tasks and their current status
Agent invocations and their outcomes (success/failure/blocked)
Test results (pass/fail counts, specific failures)
Unresolved blockers or questions awaiting user input
The current task and what step we are on

1.2 KiB Raw Blame History

Context Management

Compaction Instructions

1.2 KiB

Raw Blame History