Code Review Checklist
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object…
$ npx skills add ukanwat/overtime --skill performance-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ukanwat/overtime performance-optimization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ukanwat/overtime.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/performance-optimization .claude/skills/performance-optimization && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "performance-optimization" agent skill from https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimization into .claude/skills/performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-optimization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ukanwat/overtime --skill performance-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ukanwat/overtime performance-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ukanwat/overtime.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/performance-optimization .agents/skills/performance-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "performance-optimization" agent skill from https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimization into .agents/skills/performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-optimization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ukanwat/overtime --skill performance-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ukanwat/overtime performance-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ukanwat/overtime.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/performance-optimization .cursor/skills/performance-optimization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "performance-optimization" agent skill from https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimization into .cursor/skills/performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-optimization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ukanwat/overtime.git --path .claude/skills/performance-optimization--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ukanwat/overtime --skill performance-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ukanwat/overtime performance-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ukanwat/overtime.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/performance-optimization .gemini/skills/performance-optimization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "performance-optimization" agent skill from https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimization into .gemini/skills/performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-optimization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ukanwat/overtime performance-optimizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ukanwat/overtime --skill performance-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ukanwat/overtime.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/performance-optimization .github/skills/performance-optimization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "performance-optimization" agent skill from https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimization into .github/skills/performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-optimization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ukanwat/overtime --skill performance-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ukanwat/overtime performance-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ukanwat/overtime.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/performance-optimization .opencode/skills/performance-optimization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "performance-optimization" agent skill from https://github.com/ukanwat/overtime/tree/main/.claude/skills/performance-optimization into .opencode/skills/performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "performance-optimization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
performance-optimizationFind and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object…
Performance Optimization is an agent skill from ukanwat/overtime. Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets. Engine- neutral method that pairs with each engine's profiler. Use when the user mentions performance, optimize, low/dropping FPS, frame drops, stutter, lag, profiler, frame budget, draw calls, batching, garbage collection/GC spikes, object…
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/profiling-and-budgets.md`). Compatibility notes: Engine-agnostic methodology; profiler/tooling notes for Godot 4.x, Unity 6, and Unreal 5. Pairs with physics-tuning and the engine skills.
It sits in Development, covering Performance optimization. The repository describes itself as: Give a coding agent a brief, not a chat, and it works on its own across sessions. Includes an example run: an open-world city built in a real game engine with no human help. In… The licence is Apache-2.0.
5 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit fc215d4. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are gdscript and csharp).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Engine-agnostic methodology; profiler/tooling notes for Godot 4.x, Unity 6, and Unreal 5. Pairs with physics-tuning and the engine skills.
From compatibility in the SKILL.md frontmatter.
Performance Optimization loads about 2.3k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 143 tokens; SKILL.md has 720 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from ukanwat/overtime at commit fc215d4, republished under its Apache-2.0 licence (© ukanwat). 720 words, ~2,300 tokens.
.claude/skills/performance-optimization/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Performance work is a measurement discipline, not a bag of tricks. The method is always the
same: profile → find the one bottleneck → fix that → measure again. This skill teaches that
loop and the highest-leverage fixes (pooling, batching, allocation control, asset budgets), and
points you at each engine's profiler. It pairs with physics-tuning for simulation cost.
When not to use: for physics jitter/tunneling/timestep specifically, use physics-tuning.
For the engine's concrete profiler UI and rendering settings, use that
engine skill (godot-export covers some build settings; engine cores cover the rest). This skill
is the cross-engine method and the shared fixes.
Most performance "fixes" applied without profiling target the wrong thing and add complexity for no gain. Do not optimize code you have not measured. Open the profiler, find the single biggest cost in a representative scene on representative hardware, and fix that. Re-measure to confirm the fix helped before moving on. Profile a release/optimized build where it matters — editor and debug builds lie (editor overhead, no compiler optimization).
target FPS → frame budget: 60 FPS = 16.67 ms | 30 FPS = 33.3 ms | 120 FPS = 8.33 ms
The WHOLE frame (CPU sim + render submit + GPU) must fit the budget; the GPU runs in parallel,
so the slower of CPU-frame and GPU-frame sets your FPS. Allocate sub-budgets, e.g. @60 FPS:
gameplay/scripts ~5 ms · physics ~3 ms · rendering(CPU submit) ~4 ms · UI/other ~2 ms · slack.
If one subsystem blows its slice, that's your target — not whatever you assumed.Godot 4.x : Debugger ▸ Profiler (script/physics time) and Monitors tab (FPS, draw calls, memory).
In code: Performance.get_monitor(Performance.TIME_PROCESS) and
Performance.get_monitor(Performance.RENDER_TOTAL_DRAW_CALLS_IN_FRAME).
Unity 6 : Profiler window (CPU/GPU/Memory/Rendering modules) + Frame Debugger for draw calls.
In code: a ProfilerRecorder tracking "CPU Main Thread Frame Time" for a HUD/log.
Unreal 5 : `stat unit` (Frame/Game/Draw/GPU ms), `stat fps`, `stat scenerendering` (draw calls);
Unreal Insights for deep traces.
# Read the split: is the Draw/GPU line the biggest, or the Game/CPU line? That decides the fix.# Bullets, particles, enemies, damage numbers: reuse a fixed set instead of instantiate()/free()
# every frame — that thrashes memory and (in C#) feeds the GC.
var _pool: Array[Node] = []
func acquire() -> Node:
var n: Node = _pool.pop_back() if not _pool.is_empty() else bullet_scene.instantiate()
n.set_process(true); n.visible = true
return n
func release(n: Node) -> void:
n.set_process(false); n.visible = false # disable + hide; DON'T free
_pool.append(n) # back to the pool for reuse
# RIGHT: pre-warm the pool at load; reuse. WRONG: instantiate()/queue_free() per shot.Each unique material/texture/state change is roughly a draw call; thousands of them stall the GPU.
- Atlas textures and share materials so sprites/meshes batch into one call.
- Identical meshes → GPU instancing (Unity), MultiMesh / MultiMeshInstance (Godot), Instanced
Static Mesh (Unreal).
- Static geometry → static batching / baking; mark non-moving objects static.
- Reduce overdraw: limit large overlapping transparent/particle layers (they re-shade pixels).
- Fewer real-time lights/shadows; bake lighting where it doesn't move.
Measure draw calls before and after — the count should drop, and so should GPU frame time.// Unity 6 (C#). Allocating every frame fills the managed heap; the GC then stalls a frame.
// WRONG (allocates each call): foreach (var e in FindObjectsOfType<Enemy>()) ... // + LINQ, new[]
// RIGHT: cache references once, reuse buffers, avoid LINQ/boxing in Update.
void Update() {
_hits = Physics.RaycastNonAlloc(ray, _hitBuffer); // reuse a preallocated array
for (int i = 0; i < _hits; i++) { /* ... */ } // no per-frame allocation
}
// Godot/GDScript: avoid building new arrays/dictionaries every frame in _process; reuse them.Update (C#) feed the GC → periodic hitches.
Cache and reuse.references/profiling-and-budgets.md.physics-tuning — simulation cost, fixed-step budget, sleeping bodies, broadphase layers.godot-export — release/build settings that affect measured performance.procedural-gen, game-ai — common CPU hotspots (generation, pathfinding) to budget and defer.roguelike, tower-defense, survival-crafting — entity-heavy genres that need pooling/budgets.© ukanwat, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in .claude/skills/performance-optimization of ukanwat/overtime.
Open the folder on GitHubat commit fc215d4
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in ukanwat/overtime, which our catalogue first saw on October 7, 2026.
Performance Optimization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Performance Optimization this skillukanwat/overtime | 387 | 1 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT | |
| LLM Torch Profiler Analysissgl-project/sglang | 37k | 2 repos | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Pycrazyguitar/pysheeet | 8.2k | — | ~886 | Automated safety check: Pass | MIT | |
| Cmux Debugging Guidemanaflow-ai/cmux | 28k | 1 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Electron Heap Snapshot Analysiskeybase/client | 9.3k | — | ~875 | Automated safety check: Pass | BSD-3-Clause |
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
sgl-project/sglang
Unified LLM torch-profiler triage skill for sglang, vllm, TensorRT-LLM, and TokenSpeed.
crazyguitar/pysheeet
Comprehensive Python programming reference covering syntax, concurrency, networking, databases, ML/LLM development, and HPC.
manaflow-ai/cmux
Covers debug logging, the Debug menu, profiling rules and runtime pitfalls for working on the cmux macOS terminal app.
keybase/client
Analyzes V8, Chrome and Electron .heapsnapshot files with Node scripts to find memory leaks, detached DOM nodes and the retainer paths that keep objects alive.
ben-manes/caffeine
Runs controlled JMH experiments on the Caffeine cache to find shared contention and hot-path waste, then reviews correctness and returns a reviewable patch.
ukanwat/overtime
Implement game audio practice — bus/mixer architecture and gain in decibels, ducking (sidechain), adaptive/dynamic music via layering and re-sequencing, SFX variation, and beat synchronization.
ukanwat/overtime
Build game cameras that feel good — 2D follow with a deadzone, look-ahead, smoothing, and level-bounds clamping; 3D third-person orbit with collision and first-person look; plus multi-target framing…
ukanwat/overtime
Build branching dialogue and narrative — a node/choice graph with conditions, variables, and localization hooks — and choose between authoring tools Ink and Yarn Spinner or a custom data-driven…
ukanwat/overtime
Design NPC and enemy decision-making with finite state machines, behavior trees, steering behaviors, and A pathfinding — engine-neutral algorithms that pair with the detected engine's navigation API.
ukanwat/overtime
Add "juice" and game feel that makes actions satisfying — screen shake, hit-stop/freeze frames, tweened/eased motion, squash & stretch, knockback, and layered audio-visual feedback — as…
ukanwat/overtime
Design and build game UI/UX — HUDs, menus, and overlays — that survive every screen: anchor- based responsive layout, resolution/aspect scaling and safe areas, keyboard/gamepad focus navigation, a…
Categories
Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object…. Performance Optimization is an agent skill from ukanwat/overtime. Find and fix game performance problems methodically — measure with the engine profiler first, reason about the frame-time budget, locate the CPU-vs-GPU bottleneck, then apply the right fix: object pooling, draw-call batching, fewer allocations/GC spikes, and asset budgets.
Performance Optimization fits situations like: the user mentions performance; low/dropping FPS; garbage collection/GC spikes; the game runs slow.
Run `npx skills add ukanwat/overtime --skill performance-optimization -a claude-code`. Or copy the skill folder (.claude/skills/performance-optimization in ukanwat/overtime) into .claude/skills/performance-optimization in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ukanwat/overtime --skill performance-optimization -a codex`. Or copy the skill folder (.claude/skills/performance-optimization in ukanwat/overtime) into .agents/skills/performance-optimization in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ukanwat/overtime --skill performance-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/performance-optimization, .gemini/skills/performance-optimization, .github/skills/performance-optimization and .opencode/skills/performance-optimization in your project.
SKILL.md names no scripts, command-line tools or credentials: Performance Optimization is instructions for the agent only. Compatibility (from SKILL.md): Engine-agnostic methodology; profiler/tooling notes for Godot 4.x, Unity 6, and Unreal 5. Pairs with physics-tuning and the engine skills..
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Performance Optimization is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Performance Optimization: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Py (crazyguitar/pysheeet, 8.2k stars) and Cmux Debugging Guide (manaflow-ai/cmux, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ukanwat (a GitHub user) maintains it in ukanwat/overtime, which has 387 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 6, 2026.
Source: ukanwat/overtime on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.