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Claude-Code-Game-Studios/.claude/docs/context-management.md
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