mirror of
https://github.com/Donchitos/Claude-Code-Game-Studios.git
synced 2026-06-27 13:01:50 +00:00
- Add new /team-live-ops skill for post-launch content planning orchestration - Expand setup-engine, code-review, create-epics-stories, prototype with additional context - Enrich team-* skills (audio, combat, level, narrative, polish, release, ui) with new phases/agents - Update architecture-decision and architecture-review with dependency ordering improvements - Minor additions to balance-check, hotfix, localize, patch-notes, perf-profile - Populate technical-preferences.md with structured configuration sections Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
116 lines
4.8 KiB
Markdown
116 lines
4.8 KiB
Markdown
---
|
|
name: perf-profile
|
|
description: "Structured performance profiling workflow. Identifies bottlenecks, measures against budgets, and generates optimization recommendations with priority rankings."
|
|
argument-hint: "[system-name or 'full']"
|
|
user-invocable: true
|
|
agent: performance-analyst
|
|
allowed-tools: Read, Glob, Grep, Bash
|
|
---
|
|
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
|
|
|
|
2. **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)
|
|
|
|
3. **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 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
|
|
|
|
4. **Generate the 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 |
|
|
|---|----------|-------|------------------|------------|
|
|
| 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]
|
|
```
|
|
|
|
5. **Output the report** with a summary: top 3 hotspots, estimated headroom vs budget, and recommended next action.
|
|
|
|
6. **Scope & Timeline Decision** — activate this phase only if any hotspot has Fix Effort rated M or L.
|
|
|
|
Present a summary of the significant-effort items:
|
|
|
|
> "The following optimizations require significant effort: [list titles and effort ratings from the Hotspots table]"
|
|
|
|
For each M/L item, ask the user to choose one of:
|
|
|
|
- **A) Implement the optimization** (estimated effort: [S/M/L] — proceed with fix now or schedule it)
|
|
- **B) Reduce feature scope to avoid the bottleneck** (run `/scope-check [feature]` to analyze the trade-offs)
|
|
- **C) Accept the performance hit and defer to Polish phase** (log it as a known issue)
|
|
- **D) Escalate to technical-director for an architectural decision** (the bottleneck warrants an ADR)
|
|
|
|
For choice B, remind the user:
|
|
> "Run `/scope-check [feature]` to see what simplifications are available without sacrificing player experience."
|
|
|
|
For choice D, note:
|
|
> "A bottleneck requiring architectural change should become a new Architecture Decision Record. Run `/architecture-decision` to capture the decision and its trade-offs."
|
|
|
|
If multiple items are deferred to Polish (choice C), record them in the report under a `### Deferred to Polish` section so they are not lost.
|
|
|
|
### 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
|