Image to Three.js Model
img2threejs/img2threejs
Rebuilds the object in a reference image as a procedural, animation-ready Three.js model written entirely in code, using staged sculpting with quality checks.
Profiles Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU hotspot recording, kernel overhead measurement.
Install Hz Simpleperf Debug
$ npx skills add meta-quest/agentic-tools --skill hz-simpleperf-debug -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install meta-quest/agentic-tools hz-simpleperf-debug --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/meta-quest/agentic-tools.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/hz-simpleperf-debug .claude/skills/hz-simpleperf-debug && 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 "hz-simpleperf-debug" agent skill from https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debug into .claude/skills/hz-simpleperf-debug/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hz-simpleperf-debug", 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/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debugType 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 meta-quest/agentic-tools --skill hz-simpleperf-debug -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install meta-quest/agentic-tools hz-simpleperf-debug --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meta-quest/agentic-tools.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/hz-simpleperf-debug .agents/skills/hz-simpleperf-debug && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "hz-simpleperf-debug" agent skill from https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debug into .agents/skills/hz-simpleperf-debug/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hz-simpleperf-debug", 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 meta-quest/agentic-tools --skill hz-simpleperf-debug -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install meta-quest/agentic-tools hz-simpleperf-debug --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meta-quest/agentic-tools.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/hz-simpleperf-debug .cursor/skills/hz-simpleperf-debug && 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 "hz-simpleperf-debug" agent skill from https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debug into .cursor/skills/hz-simpleperf-debug/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hz-simpleperf-debug", 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/meta-quest/agentic-tools.git --path skills/hz-simpleperf-debug--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 meta-quest/agentic-tools --skill hz-simpleperf-debug -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install meta-quest/agentic-tools hz-simpleperf-debug --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meta-quest/agentic-tools.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/hz-simpleperf-debug .gemini/skills/hz-simpleperf-debug && 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 "hz-simpleperf-debug" agent skill from https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debug into .gemini/skills/hz-simpleperf-debug/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hz-simpleperf-debug", 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 meta-quest/agentic-tools hz-simpleperf-debugInstalls 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 meta-quest/agentic-tools --skill hz-simpleperf-debug -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/meta-quest/agentic-tools.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/hz-simpleperf-debug .github/skills/hz-simpleperf-debug && 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 "hz-simpleperf-debug" agent skill from https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debug into .github/skills/hz-simpleperf-debug/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hz-simpleperf-debug", 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 meta-quest/agentic-tools --skill hz-simpleperf-debug -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install meta-quest/agentic-tools hz-simpleperf-debug --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/meta-quest/agentic-tools.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/hz-simpleperf-debug .opencode/skills/hz-simpleperf-debug && 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 "hz-simpleperf-debug" agent skill from https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-simpleperf-debug into .opencode/skills/hz-simpleperf-debug/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hz-simpleperf-debug", 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.
Facts
- Skill name
hz-simpleperf-debug- GitHub stars
- 213
- Token cost
- ~2k tokens
- SKILL.md length
- 804 words
- Files
- 4 (incl. references)
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Profiles Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU hotspot recording, kernel overhead measurement.
- Works in 6 steps: Classify the Workload → Record CPU Hotspots → Measure Kernel Overhead → …
- Diagnosing whether an app is CPU-bound
- SKILL.md covers When to Use, VR Performance Context, metavr Setup and Quick Start Workflow, plus 3 more sections
- Calls npx and adb
What it does
Hz Simpleperf Debug is an agent skill from meta-quest/agentic-tools. Profiles Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU hotspot recording, kernel overhead measurement. Use when diagnosing whether an app is CPU-bound, memory-bound, or I/O-bound on Meta VR devices. Build paths: all Meta VR app stacks; use hz-quest-verify-first if the build path is unclear.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/cpu-hotspot-analysis.md`, `references/kernel-overhead.md` and `references/workload-classification.md`).
It sits in Game Development. The repository describes itself as: Agent Skills for Meta Quest/Horizon OS VR Development. The licence is Apache-2.0.
When your agent uses it
- Diagnosing whether an app is CPU-bound
- I/O-bound on Meta VR devices
Example prompts
- “Use the hz-simpleperf-debug skill to profile Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU…”
- “/hz-simpleperf-debug”
Requirements
- Node.js
- Pre-approved tools (allowed-tools): Bash(metavr:*), Bash(hzdb:*)
Workflow steps
6 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 3a8553d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
Bash(metavr:*)Bash(hzdb:*)
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
npxadb
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Hz Simpleperf Debug loads about 2k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 91 tokens; SKILL.md has 804 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from meta-quest/agentic-tools at commit 3a8553d, republished under its Apache-2.0 licence (© meta-quest). 804 words, ~1,953 tokens.
Download SKILL.mdSave it as
.claude/skills/hz-simpleperf-debug/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- hz-simpleperf-debug
- description
- Profiles Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU hotspot recording, kernel overhead measurement. Use when diagnosing whether an app is CPU-bound, memory-bound, or I/O-bound on Meta VR devices. Build paths: all Meta VR app stacks; use hz-quest-verify-first if the build path is unclear.
- allowed-tools
- Bash(metavr:*), Bash(hzdb:*)
- license
- Apache-2.0
Simpleperf Debug Skill
When to Use
Use this skill when you need hardware-level CPU performance insights on Meta VR devices:
- Classifying whether an app is CPU-bound, memory-bound, or I/O-bound
- Finding CPU hotspot functions consuming the most cycles
- Measuring kernel vs userspace CPU overhead per thread
- Identifying cache-thrashing or branch-prediction issues
- Supplementing Perfetto trace analysis with hardware PMU counter data
This skill complements hz-perfetto-debug. Perfetto shows what your app is doing over time. Simpleperf shows where the CPU is spending hardware cycles — cache misses, branch mispredictions, and instruction throughput that Perfetto can't see.
VR Performance Context
Meta VR devices run on mobile ARM SoCs with strict thermal and power budgets. CPU-bound apps hit frame drops when:
| Refresh Rate | CPU Frame Budget | Notes |
|---|---|---|
| 120 Hz | 8.3 ms | Tight — simpleperf critical for finding hotspots |
| 90 Hz | 11.1 ms | Default target for most apps |
| 72 Hz | 13.9 ms | Fallback for heavier apps |
Simpleperf's hardware counters reveal bottlenecks invisible to software tracing.
metavr Setup
Simpleperf profiling is powered by the metavr CLI — install the standalone binary on your PATH (see the metavr-cli skill), or invoke via npx with no install:
metavr --versionExamples below use the bare metavr command; if you use the npm distribution, prefix with npx -y. Connect your Meta VR device via USB with developer mode enabled.
Quick Start Workflow
1. Classify the Workload
Before optimizing, determine the bottleneck type:
# Classify the foreground app's workload (10-second sample)
metavr perf simpleperf classify
# Target a specific app
metavr perf simpleperf classify --app com.example.myapp
# Custom duration
metavr perf simpleperf classify --duration 15Returns a classification with evidence:
| Classification | Indicator | Optimization Strategy |
|---|---|---|
| CPU-bound | High IPC, low stall ratio | Optimize algorithms, reduce draw calls, batch work |
| Memory-bound | High stall ratio (stalled-cycles-backend / cpu-cycles) | Reduce cache misses, improve data locality, shrink working set |
| I/O-bound | High context switches per second | Reduce blocking I/O, use async, minimize thread contention |
2. Record CPU Hotspots
Capture a CPU cycle profile to find the most expensive functions:
# Record CPU hotspots for the foreground app
metavr perf simpleperf record
# Custom frequency and duration
metavr perf simpleperf record --frequency 4000 --duration 10
# Target a specific app
metavr perf simpleperf record --app com.example.myappThe recording samples CPU cycles at the specified frequency (default 4000 Hz) and generates a profile showing which functions consume the most CPU time.
3. Measure Kernel Overhead
Determine how much CPU time is spent in kernel vs userspace per thread:
# Measure kernel overhead for the foreground app
metavr perf simpleperf kernel-overhead
# Custom duration
metavr perf simpleperf kernel-overhead --app com.example.myapp --duration 10Returns per-thread breakdown of user-mode vs kernel-mode CPU cycles. High kernel overhead (>20%) in a thread suggests:
- Excessive syscalls (file I/O, memory allocation)
- Driver overhead (GPU command submission, sensor access)
- Lock contention in kernel synchronization primitives
Analysis Workflow
Step 1: Classify First
Always start with classification. This prevents wasting time optimizing the wrong thing.
metavr perf simpleperf classify --app com.example.myapp --duration 10Decision tree based on results:
- CPU-bound → Record hotspots (Step 2a), look at top functions
- Memory-bound → Record with cache-miss events, check data access patterns
- I/O-bound → Check kernel overhead, look at thread contention in Perfetto
Step 2a: CPU-Bound Apps — Find Hotspots
metavr perf simpleperf record --app com.example.myapp --duration 10Review the top functions by CPU cycle consumption. Common VR hotspots:
| Function Pattern | Likely Cause | Fix |
|---|---|---|
Physics.* / PhysX | Complex physics simulation | Reduce collider count, simplify meshes, increase fixed timestep |
Render* / Draw* | Too many draw calls | Batch materials, use GPU instancing, reduce unique materials |
GC_* / gc_alloc | Garbage collection pressure | Pool allocations, avoid per-frame allocations |
memcpy / memmove | Large data copies | Use references, reduce buffer sizes, avoid unnecessary copies |
LZ4_* / compress | Asset decompression | Pre-decompress, use lighter compression, cache results |
Show full SKILL.md (302 more words)Show less
Step 2b: Memory-Bound Apps — Check Cache Behavior
If classification shows memory-bound, the issue is likely cache misses or memory bandwidth:
- Large working sets thrashing L1/L2 cache
- Random access patterns defeating prefetcher
- False sharing between threads on adjacent cache lines
Use Perfetto hz-perfetto-debug to correlate memory-bound regions with specific code paths.
Step 3: Measure Kernel Overhead
metavr perf simpleperf kernel-overhead --app com.example.myappInterpreting results by thread:
| Thread | Expected Kernel % | High Kernel % Indicates |
|---|---|---|
| Main/Game thread | < 5% | Excessive file I/O, logging, or allocations |
| Render thread | 5-15% | Normal (GPU driver overhead). >20% = driver issue |
| Worker threads | < 5% | Thread synchronization overhead |
| Audio thread | < 10% | Normal for audio HAL calls |
Step 4: Combine with Perfetto
Simpleperf tells you where cycles go. Perfetto tells you when and in what context. Use together:
- Simpleperf classification reveals the bottleneck type
- Simpleperf hotspot recording identifies the expensive functions
- Perfetto trace (
metavr perf capture) shows when those functions run relative to frame boundaries - Use
metavr perf queryto correlate function timing with frame drops
Common Pitfalls
- Don't profile in thermal throttling. Let the device cool before recording — throttled clocks distort cycle counts. Check thermal state first with
metavr device info. - Sample duration matters. Short recordings (<5s) may not capture representative behavior. Use at least 10 seconds for classification.
- simpleperf requires shell access. If
adb shell simpleperffails, ensure developer mode is enabled and USB debugging is authorized. - Frequency vs accuracy tradeoff. Higher sampling frequency (>8000 Hz) can perturb the workload on mobile SoCs. Default 4000 Hz is a good balance.
- Classification is a snapshot. An app can be CPU-bound during gameplay and I/O-bound during scene loads. Profile the specific scenario you're optimizing.
References
For detailed guides on specific topics, see:
- Workload Classification — PMU counter interpretation and bottleneck identification
- CPU Hotspot Analysis — Recording and analyzing CPU cycle profiles
- Kernel Overhead — Measuring and reducing kernel-mode CPU usage
© meta-quest, 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
Files
SKILL.md and 3 other files (references) in skills/hz-simpleperf-debug of meta-quest/agentic-tools.
- SKILL.md
- references/cpu-hotspot-analysis.md
- references/kernel-overhead.md
- references/workload-classification.md
Open the folder on GitHubat commit 3a8553d
Compare with similar skills
Hz Simpleperf Debug 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 |
|---|---|---|---|---|---|---|
| Hz Simpleperf Debug this skillmeta-quest/agentic-tools | 213 | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Image to Three.js Modelimg2threejs/img2threejs | 18k | 1 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 | |
| Web CloneJane-xiaoer/claude-skill-web-clone | 1k | 1 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Threejs Game Directormajidmanzarpour/threejs-game-skills | 2.4k | — | ~2.2k | Automated safety check: Pass | MIT | |
| Game Asset Generatorhtdt/godogen | 7.1k | — | ~2.8k | Automated safety check: Pass | MIT | |
| Threejs Gameplay Systemsvalkor-ai/loom | 1.2k | 1 repos | ~1.4k | Automated safety check: Pass | Apache-2.0 |
Similar skills
Web Clone
Jane-xiaoer/claude-skill-web-clone
网站复刻 / 克隆方法论。USE WHEN 用户说 复刻网站、克隆网站、clone website、抄个站、仿站、 照着这个站做一个、reproduce site、还原某个网页效果、把这个站搬下来改成我的、 复刻某个交互/WebGL/Canvas/Three.js 效果。提供「先拿真源码 → 判路径 → 逆向拆解 → 搭工程 → 替换内容」的可移植决策树，覆盖静态站 /…
Threejs Game Director
majidmanzarpour/threejs-game-skills
Entrypoint for building, upgrading, and finishing Three.js browser games.
Game Asset Generator
htdt/godogen
Generates game art from text prompts: PNG images, GLB 3D models, rigged characters, animations and sprites, with background removal.
Threejs Gameplay Systems
valkor-ai/loom
Build and iterate playable Three.js game systems: starter scaffold, architecture, design briefs, core loops, level and encounter design, entities, input, camera, collision and physics, scoring…
Uloop Execute Dynamic Code
CyberAgentGameEntertainment/NovaShader
Execute C with Unity APIs when existing uloop tools cannot inspect or edit enough.
More from meta-quest/agentic-tools
All 34 skills in this repoHz Android 2D Porting
meta-quest/agentic-tools
Guides porting existing Android 2D apps to Meta VR and Horizon OS — input adaptation, panel layout, and design requirements.
Hz API Upgrade
meta-quest/agentic-tools
Upgrades Meta VR apps to newer Horizon OS SDK versions — migration guides, deprecated API replacements, changelog.
Hz Iwsdk Webxr
meta-quest/agentic-tools
Builds WebXR experiences for Meta VR and Horizon OS using the Immersive Web SDK (IWSDK) — ECS architecture, Three.js integration, spatial UI.
Hz Metavrx Layout SDK
meta-quest/agentic-tools
Build multi-window Meta Horizon OS experiences with the MetaVrx Layout SDK in Jetpack Compose or React Native.
Hz New Project Creation
meta-quest/agentic-tools
Scaffolds new Meta VR and Horizon OS projects after the build path is selected — Standard Android, Meta Spatial SDK, Unity, Unreal, or WebXR.
Hz Perfetto Debug
meta-quest/agentic-tools
Analyzes Meta VR and Horizon OS VR performance using Perfetto traces — frame timing, CPU/GPU bottlenecks, render pass analysis.
Related
Categories
Questions about Hz Simpleperf Debug
What does Hz Simpleperf Debug do?
Profiles Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU hotspot recording, kernel overhead measurement. Hz Simpleperf Debug is an agent skill from meta-quest/agentic-tools. Profiles Meta VR and Horizon OS application CPU performance using simpleperf — workload classification, CPU hotspot recording, kernel overhead measurement.
When should I use Hz Simpleperf Debug?
Hz Simpleperf Debug fits situations like: diagnosing whether an app is CPU-bound; I/O-bound on Meta VR devices.
How do I install Hz Simpleperf Debug in Claude Code?
Run `npx skills add meta-quest/agentic-tools --skill hz-simpleperf-debug -a claude-code`. Or copy the skill folder (skills/hz-simpleperf-debug in meta-quest/agentic-tools) into .claude/skills/hz-simpleperf-debug in your project. Claude Code loads it when a task matches its description.
How do I install Hz Simpleperf Debug in Codex?
Run `npx skills add meta-quest/agentic-tools --skill hz-simpleperf-debug -a codex`. Or copy the skill folder (skills/hz-simpleperf-debug in meta-quest/agentic-tools) into .agents/skills/hz-simpleperf-debug in your project. Codex loads it when a task matches its description.
Can I use Hz Simpleperf Debug in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add meta-quest/agentic-tools --skill hz-simpleperf-debug -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hz-simpleperf-debug, .gemini/skills/hz-simpleperf-debug, .github/skills/hz-simpleperf-debug and .opencode/skills/hz-simpleperf-debug in your project.
What does Hz Simpleperf Debug need to run?
Going by SKILL.md and its folder, Hz Simpleperf Debug needs the command-line tools its instructions call (npx and adb). Our summary lists: Node.js. Its frontmatter pre-approves these tools: Bash(metavr:*), Bash(hzdb:*).
Does Hz Simpleperf Debug access the network?
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Hz Simpleperf Debug safe to install?
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.
What licence does Hz Simpleperf Debug use?
Hz Simpleperf Debug 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.
How many tokens does Hz Simpleperf Debug use?
About 2k tokens (SKILL.md is roughly 7.8k 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 3.1k tokens, read only when the agent opens those files.
What are the alternatives to Hz Simpleperf Debug?
Skills that share tags, products or a category with Hz Simpleperf Debug: Image to Three.js Model (img2threejs/img2threejs, 18k stars), Web Clone (Jane-xiaoer/claude-skill-web-clone, 1k stars), Threejs Game Director (majidmanzarpour/threejs-game-skills, 2.4k stars) and Game Asset Generator (htdt/godogen, 7.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Hz Simpleperf Debug?
meta-quest (a GitHub organization) maintains it in meta-quest/agentic-tools, which has 213 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on September 24, 2026.
Source: meta-quest/agentic-tools on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.