perf-profile— agent skill

When this skill is invoked:

1. Determine scope from the argument:

• If a system name: focus profiling on that specific system
• If full: run a comprehensive profile across all systems

1. Read performance budgets — Check for existing performance targets in design docs or CLAUDE.md:

• Target FPS (e.g., 60fps = 16.67ms frame budget)
• Memory budget (total and per-system)
• Load time targets
• Draw call budgets
• Network bandwidth limits (if multiplayer)

1. Analyze the codebase for common performance issues:

CPU Profiling Targets:

• _process() / Update() / Tick() functions — list all and estimate cost
• Nested loops over large collections
• String operations in hot paths
• Allocation patterns in per-frame code
• Unoptimized search/sort over data entities
• Expensive physics queries (raycasts, overlaps) every frame

Memory Profiling Targets:

• Large data structures and their growth patterns
• Texture/asset memory footprint estimates
• Object pool vs instantiate/destroy patterns
• Leaked references (objects that should be freed but aren't)
• Cache sizes and eviction policies

Rendering Targets (if applicable):

• Draw call estimates
• Overdraw from overlapping transparent objects
• Shader complexity
• Unoptimized particle systems
• Missing LODs or occlusion culling

I/O Targets:

• Save/load performance
• Asset loading patterns (sync vs async)
• Network message frequency and size

1. Generate the profiling report:

   ## Performance Profile: [System or Full]
   Generated: [Date]

   ### Performance Budgets
   | Metric | Budget | Estimated Current | Status |
   |--------|--------|-------------------|--------|
   | Frame time | [16.67ms] | [estimate] | [OK/WARNING/OVER] |
   | Memory | [target] | [estimate] | [OK/WARNING/OVER] |
   | Load time | [target] | [estimate] | [OK/WARNING/OVER] |
   | Draw calls | [target] | [estimate] | [OK/WARNING/OVER] |

   ### Hotspots Identified
   | # | Location | Issue | Estimated Impact | Fix Effort |
   |---|----------|-------|------------------|------------|
   | 1 | [file:line] | [description] | [High/Med/Low] | [S/M/L] |
   | 2 | [file:line] | [description] | [High/Med/Low] | [S/M/L] |

   ### Optimization Recommendations (Priority Order)
   1. **[Title]** — [Description of the optimization]
      - Location: [file:line]
      - Expected gain: [estimate]
      - Risk: [Low/Med/High]
      - Approach: [How to implement]

   ### Quick Wins (< 1 hour each)
   - [Simple optimization 1]
   - [Simple optimization 2]

   ### Requires Investigation
   - [Area that needs actual runtime profiling to determine impact]

1. Output the report with a summary: top 3 hotspots, estimated headroom vs budget, and recommended next action.

Rules

• Never optimize without measuring first — gut feelings about performance are unreliable
• Recommendations must include estimated impact — "make it faster" is not actionable
• Profile on target hardware, not just development machines
• Distinguish between CPU-bound, GPU-bound, and I/O-bound bottlenecks
• Consider worst-case scenarios (maximum entities, lowest spec hardware, worst network conditions)
• Static analysis (this skill) identifies candidates; runtime profiling confirms

Protocol

• Question: Reads system name or full from argument
• Options: Skip
• Decision: Skip
• Draft: Profile report shown in conversation only
• Approval: Skip — read-only; no files written by default

Output

Deliver exactly:

• Top 3 hotspots — system, estimated impact, and recommended fix
• Budget headroom — actual vs target for each metric in technical-preferences.md
• Optimization priority list — ranked by impact/effort ratio
• Next action: PROFILE CONFIRMED (static analysis sufficient) or RUNTIME PROFILING NEEDED (list what to measure)