perf-profile

Original：🇺🇸 English

Translated

Structured performance profiling workflow. Identifies bottlenecks, measures against budgets, and generates optimization recommendations with priority rankings.

5installs

Sourcedonchitos/claude-code-game-studios

Added on2026-05-27

NPX Install

npx skill4agent add donchitos/claude-code-game-studios perf-profile

SKILL.md Content

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Phase 1: Determine Scope

Read the argument:

System name → focus profiling on that specific system
```
full
```
→ run a comprehensive profile across all systems

Phase 2: Load 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)

Phase 3: Analyze Codebase

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 game 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

Phase 4: Generate Profiling Report

markdown

## 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 |
|---|----------|-------|------------------|------------|

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

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

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

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

Phase 5: Scope and Timeline Decision

Activate this phase only if any hotspot has Fix Effort rated M or L.

Present significant-effort items and ask the user to choose for each:

A) Implement the optimization (proceed with fix now or schedule it)
B) Reduce feature scope (run
```
/scope-check [feature]
```
to analyze trade-offs)
C) Accept the performance hit and defer to Polish phase (log as known issue)
D) Escalate to technical-director for an architectural decision (run
```
/architecture-decision
```
)

If multiple items are deferred to Polish (choice C), record them under

### Deferred to Polish

.

This skill is read-only — no files are written. Verdict: COMPLETE — performance profile generated.

Phase 6: Next Steps

If bottlenecks require architectural change: run
```
/architecture-decision
```
.
If scope reduction is needed: run
```
/scope-check [feature]
```
.
To schedule optimizations: run
```
/sprint-plan update
```
.

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
Static analysis (this skill) identifies candidates; runtime profiling confirms