Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add striderZA/OpenCodeGameStudios --skill perf-profilegit clone --depth 1 https://github.com/striderZA/OpenCodeGameStudiosWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/striderza/opencodegamestudios/perf-profile)<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/perf-profile"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/perf-profile/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/striderza/opencodegamestudios/perf-profile"><img src="https://agentmods.dev/badge/skills/striderza/opencodegamestudios/perf-profile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00026 | $0.00938 |
| Opus 5.5 | $0.00010 | $0.00375 |
| Sonnet 5.5 | $0.00005 | $0.00188 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
perf-profile scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to perf-profile — 134 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 AGENTS.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
## 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]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 126 lines · 26 tokens per session scan A 2f94c7692c4f
perf-profile is a skill published in the GitHub repository striderZA/OpenCodeGameStudios (99 stars, last pushed 13d ago), licensed MIT. It adds 26 tokens to every session and 938 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to perf-profile, differing in 134 lines, and is treated as a copy.
Other skills, from other repositories
professional-game-developer
Universal production game engineering skill — design, build, profile, test, and ship games across Unreal Engine 5, Unity 6 (DOTS), Godot 4.3+, Roblox (Luau), and Web/Custom engines with senior studio-grade architectural discipline. Encompasses all 42 specialized game studio job roles across 6 departments: Game Design…
design-system
Guided, section-by-section GDD authoring for a single game system. Gathers context from existing docs, walks through each required section collaboratively, cross-references dependencies, and writes incrementally to file.
setup-engine
Configure the project's game engine and version. Pins the engine in OPENCODE.md, detects knowledge gaps, and populates engine reference docs via WebSearch when the version is beyond the LLM's training data.
gate-check
Validate readiness to advance between development phases. Produces a PASS/CONCERNS/FAIL verdict with specific blockers and required artifacts.
reverse-document
Generate design or architecture documents from existing implementation. Works backwards from code/prototypes to create missing planning docs.
estimate
Estimates task effort by analyzing complexity, dependencies, historical velocity, and risk factors. Produces a structured estimate with confidence levels.