memory-budgeting

Memory Budgeting

Purpose

Define residency and memory budgets so content, streaming, and runtime systems fit target platforms.

Use When

• the project has constrained hardware targets
• memory spikes cause instability
• large content sets are growing

Inputs

• target platforms
• asset classes
• streaming model
• system residency assumptions

Process

1. budget memory by asset and system class
2. define who owns loading and unloading decisions
3. measure peak and steady-state memory in representative flows
4. flag accidental hard references or pinned content
5. connect fixes to content and architecture owners

Outputs

• memory budget sheet
• residency rules
• peak-memory review notes
• ownership map

Quality Bar

• makes ownership, state flow, and failure behavior explicit
• improves maintainability without over-abstracting
• supports testing, debugging, and safe iteration

Common Failure Modes

• coupling systems through hidden globals or timing assumptions
• writing logic that is hard to test or debug
• optimizing the wrong layer before measuring

Related Agents

• performance-reviewer
• technical-artist
• build-engineer

Related Commands

• memory-budget
• verify
• release-check

Notes

• Keep this skill aligned with the relevant rules layer and current project documentation.
• If engine-specific constraints materially change the workflow, hand off to the matching engine skill or engine-specific reviewer.