Agent skill

Auv Wayland Rendering

by moeru-ai in moeru-ai/auv

Prepare, diagnose, and validate Linux GPU and Wayland environments for AUV rendering and capture through XDG Desktop Portal and PipeWire.

Apache-2.0Auto-check passedProductivity & Automation

Install Auv Wayland Rendering

skills CLI
$ npx skills add moeru-ai/auv --skill auv-wayland-rendering -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install moeru-ai/auv auv-wayland-rendering --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/moeru-ai/auv.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/auv-wayland-rendering .claude/skills/auv-wayland-rendering && rm -rf skills-src

Use ~/.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/

Facts

Skill name
auv-wayland-rendering
GitHub stars
100
Token cost
~1.7k tokens
SKILL.md length
829 words
Files
7 (incl. scripts, references)
Repo updated
First seen
Licence
Apache-2.0

At a glance

Prepare, diagnose, and validate Linux GPU and Wayland environments for AUV rendering and capture through XDG Desktop Portal and PipeWire.

  • Works in 6 steps: Inspect before changing the host → Choose the session shape → Install the smallest capability set → …
  • Installing AUV desktop runtime dependencies
  • SKILL.md covers Read the relevant references, Follow the workflow and Apply safety rules
  • Runs Shell scripts from its folder; calls cargo

What it does

Auv Wayland Rendering is an agent skill from moeru-ai/auv. Prepare, diagnose, and validate Linux GPU and Wayland environments for AUV rendering and capture through XDG Desktop Portal and PipeWire. Use when installing AUV desktop runtime dependencies, connecting from another machine over SSH, using an existing compositor or a headless wlroots/Sway session, checking hardware versus software rendering, running display.capture or Linux driver probes, exposing optional WayVNC safely, or troubleshooting blank frames and Wayland, portal, D-Bus, PipeWire, or session-environment…

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including scripts and reference files (for example `agents/openai.yaml`, `references/setup.md` and `references/troubleshooting.md`).

It sits in Productivity & Automation. It works with Linux. The repository describes itself as: 📱🐭 No we are not computer use, it's Application Use Via... a unified orchestration layer of OS automation, 0 token cost. The licence is Apache-2.0.

When your agent uses it

  • Installing AUV desktop runtime dependencies
  • Connecting from another machine over SSH
  • Using an existing compositor
  • A headless wlroots/Sway session

Example prompts

  • “/auv-wayland-rendering”

Requirements

  • A Bash shell

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Inspect before changing the host
  2. Choose the session shape
  3. Install the smallest capability set
  4. Keep one coherent user session
  5. Validate from dependencies to AUV artifacts
  6. Report the boundary precisely

What it can do on your machine

Read from SKILL.md and the folder at commit 4042350. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 3 files in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • cargo

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Auv Wayland Rendering loads about 1.7k tokens when it runs, and up to ~4.4k if it reads all its reference files. Until then it costs about 137 tokens; SKILL.md has 829 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~137
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.4k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from moeru-ai/auv at commit 4042350, republished under its Apache-2.0 licence (© moeru-ai). 829 words, ~1,708 tokens.

Download SKILL.mdSave it as .claude/skills/auv-wayland-rendering/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
auv-wayland-rendering
description
Prepare, diagnose, and validate Linux GPU and Wayland environments for AUV rendering and capture through XDG Desktop Portal and PipeWire. Use when installing AUV desktop runtime dependencies, connecting from another machine over SSH, using an existing compositor or a headless wlroots/Sway session, checking hardware versus software rendering, running display.capture or Linux driver probes, exposing optional WayVNC safely, or troubleshooting blank frames and Wayland, portal, D-Bus, PipeWire, or session-environment failures.

AUV Wayland Rendering

Build a reproducible Linux desktop session in which AUV can observe a Wayland display and persist capture artifacts. Treat environment validation as evidence, not as a change to AUV's public support claim.

Keep ownership explicit: the compositor renders application clients; AUV requests frames through the portal and records them. Do not imply that AUV ships the compositor or a Linux overlay renderer.

Read the relevant references

  • Read setup.md before installing packages, creating a compositor session, or configuring remote viewing.
  • Read troubleshooting.md when a probe or capture fails, the image is blank, or hardware rendering is uncertain.
  • Check AUV's current support matrix before describing a result as supported. A successful live probe is live-validated evidence for the named environment only.

Follow the workflow

1. Inspect before changing the host

Run the read-only probe in the target shell:

bash
.agents/skills/auv-wayland-rendering/scripts/probe-wayland.sh

Add --require-gpu to make missing GPU prerequisites fatal when hardware rendering is required. The flag does not replace compositor-log evidence. Record:

  • distribution and package manager;
  • existing compositor and whether the session is local, nested, or headless;
  • WAYLAND_DISPLAY, XDG_RUNTIME_DIR, and the session D-Bus;
  • accessible /dev/dri/renderD* nodes and the renderer reported by compositor logs or eglinfo/vulkaninfo;
  • ScreenCast portal and PipeWire readiness.

Do not infer GPU rendering from the presence of a GPU or render node. Require a renderer log or renderer-tool result. Label pixman, llvmpipe, and similar paths as software rendering.

2. Choose the session shape

Prefer the existing logged-in Wayland compositor when one is available. It already owns the seat, GPU, D-Bus activation environment, and user consent UI.

Use headless Sway when the host has no desktop session or the test must be isolated. Start with wlroots renderer auto-selection. Force pixman only as an explicit software fallback; doing so gives deterministic rendering but does not validate the GPU path.

Use a nested compositor when isolation is needed inside an existing Wayland desktop and an extra window is acceptable. Do not point AUV at one compositor while its portal backend is attached to another.

3. Install the smallest capability set

Install or verify:

  • a Wayland compositor such as Sway;
  • xdg-desktop-portal and the backend for that compositor;
  • PipeWire and WirePlumber;
  • wayland-info and grim for independent diagnostics;
  • WayVNC only when a human needs to view the wlroots session remotely.

Request authorization before changing system packages, user services, group membership, login linger, or firewall state. Prefer distribution packages. Use a source build or patch only after reproducing a version-specific defect and recording the exact upstream revision and reason.

4. Keep one coherent user session

Run the compositor, portal backend, PipeWire, and AUV as the same unprivileged user. They must agree on XDG_RUNTIME_DIR, WAYLAND_DISPLAY, and the session bus. For a compositor started by a user service, import its generated variables into the systemd user manager and retrieve them in SSH shells.

Use the helper to run a command with either the current environment or the variables published by the user manager:

bash
.agents/skills/auv-wayland-rendering/scripts/with-wayland-session.sh \
  auv invoke display.list --json

Do not run the compositor or AUV as root to work around device permissions. Fix seat, logind, container-device, or render-node access instead.

Show full SKILL.md (338 more words)Show less
5. Validate from dependencies to AUV artifacts

Validate in this order so each failure has one clear owner:

  1. Confirm the Wayland socket and compositor output with wayland-info or the compositor IPC.

  2. Confirm PipeWire and the org.freedesktop.portal.ScreenCast interface.

  3. Run the AUV Linux driver probe:

    bash
    cargo run -p auv-driver-linux --example validate -- permissions displays
  4. Run repeated product-surface captures:

    bash
    .agents/skills/auv-wayland-rendering/scripts/verify-auv-capture.sh \
      --auv target/debug/auv --repeat 3
  5. Open at least one emitted PNG. Verify that it contains the expected client, has the expected dimensions, and is not a blank or stale frame.

Repeated captures establish startup and first-frame reliability. To test freshness, visibly change a client between two capture passes and compare their artifacts; identical static frames do not prove that updates propagate.

The verification script checks AUV's JSON result, artifact purpose, PNG signature, and file existence. It does not prove semantic correctness of the rendered application; visual inspection or an app-specific assertion remains separate.

6. Report the boundary precisely

Report all of the following:

  • OS, compositor, portal backend, output name and dimensions;
  • renderer and whether it is hardware or software;
  • portal frame transport when known (dma-buf, shared memory, or fallback);
  • AUV revision and exact validation commands;
  • successful run IDs and artifact paths;
  • whether remote viewing was enabled and how it was secured;
  • known warnings, fallbacks, and missing capabilities.

Do not turn compilation, a portal introspection result, or a single screenshot into a blanket Linux support claim.

Keep GPU compositor rendering, GPU-buffer transport, and correct AUV artifact output as three separate claims. None implies the other two.

Apply safety rules

  • Bind WayVNC to loopback and use an SSH tunnel unless authenticated transport was explicitly configured.
  • Do not expose an unauthenticated VNC port on 0.0.0.0.
  • Do not overwrite an existing desktop's portal selection without checking its current backend and other consumers.
  • Do not persist services or enable login linger unless the user requested a durable session.
  • Keep capture and input evidence separate. A rendered frame does not prove that input was delivered or that an application completed an operation.

© moeru-ai, 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 6 other files (scripts, references) in .agents/skills/auv-wayland-rendering of moeru-ai/auv.

  • SKILL.md
  • agents/openai.yaml
  • references/setup.md
  • references/troubleshooting.md
  • scripts/probe-wayland.sh
  • scripts/verify-auv-capture.sh
  • scripts/with-wayland-session.sh

Open the folder on GitHubat commit 4042350

Compare with similar skills

Auv Wayland Rendering 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.

Auv Wayland Rendering compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Auv Wayland Rendering this skillmoeru-ai/auv100—~1.7kAutomated safety check: PassApache-2.0
Cloud Computer Usedavidondrej/cloudroom-core285—~881Automated safety check: NotesApache-2.0
Gui Onboarding Verification Skillwarpdotdev/warp65k1 repos~6.2kAutomated safety check: PassAGPL-3.0
Daily UpdateAr9av/obsidian-wiki3.5k—~2.4kAutomated safety check: NotesMIT
Eradicating Malware From Infected Systemsmukul975/Anthropic-Cybersecurity-Skills34k—~2.2kAutomated safety check: WarnApache-2.0
Linux System HealthLeoYeAI/openclaw-master-skills2.2k—~5kAutomated safety check: PassMIT

Similar skills

  • Cloud Computer Use

    davidondrej/cloudroom-core

    See and control desktop apps on this Cloud sandbox’s virtual Linux screen with cloudroom computer-use: launch GUI apps you build or install, read their UI, click, type, and take screenshots.

    285 GitHub stars~881 tokensUpdated today
    Productivity & AutomationAuto-check: notes
  • GUI desktop app only. An agent skill from warpdotdev/warp.

    65k GitHub starsUsed in 1 repo~6.2k tokens
    Productivity & AutomationAuto-check passed
  • Daily Update

    Ar9av/obsidian-wiki

    Run or configure the daily wiki maintenance cycle: check source freshness, refresh the index and hot.md, and manage its scheduled 9 AM launchd/systemd/cron reminder.

    3.5k GitHub stars~2.4k tokensUpdated today
    Productivity & AutomationAuto-check: notes
  • Eradicating Malware From Infected Systems

    mukul975/Anthropic-Cybersecurity-Skills

    Systematically map and remove malware, backdoors, and attacker persistence mechanisms (registry Run keys, scheduled tasks, WMI subscriptions, services, cron/init.d) from infected Windows and Linux…

    34k GitHub stars~2.2k tokensUpdated 1 mo ago
    Productivity & AutomationAuto-check: warnings
  • Linux System Health

    LeoYeAI/openclaw-master-skills

    Diagnose Linux OS-level issues — slow server, OOM kills, disk full, high CPU/load, DNS failures, connection timeouts, port exhaustion, too many open files, zombie processes, browser automation…

    2.2k GitHub stars~5k tokensUpdated 2 mo ago
    Productivity & AutomationAuto-check passed
  • Open Computer Use

    iFurySt/open-codex-computer-use

    Platform-neutral guidance for using Open Computer Use, the open-source Computer Use MCP server and CLI for macOS, Linux, and Windows.

    2.4k GitHub stars~1.5k tokensUpdated today
    Productivity & AutomationAuto-check passed

More from moeru-ai/auv

All 8 skills in this repo
  • Use Buf

    moeru-ai/auv

    Configure, inspect, update, validate, and troubleshoot Buf workspaces and modules.

    100 GitHub stars~1k tokensUpdated today
    Auto-check passed
  • Domain CLI

    moeru-ai/auv

    A skill your agent uses when building CLI tools. An agent skill from moeru-ai/auv.

    100 GitHub starsUsed in 1 repo~988 tokens
    Auto-check passed
  • Use Protobuf

    moeru-ai/auv

    Design, change, and review Protobuf schemas used as gRPC contracts, streaming protocols, typed data models, grpc-gateway REST APIs, OpenAPI specifications, or generated SDK inputs.

    100 GitHub stars~1.6k tokensUpdated today
    Auto-check passed
  • A skill your agent uses when building cloud-native apps. An agent skill from moeru-ai/auv.

    100 GitHub starsUsed in 1 repo~1k tokens
    Auto-check passed
  • Domain ML

    moeru-ai/auv

    A skill your agent uses when building ML/AI apps in Rust. An agent skill from moeru-ai/auv.

    100 GitHub starsUsed in 1 repo~1.2k tokens
    Auto-check passed
  • Use Pixi

    moeru-ai/auv

    A skill your agent uses when explaining, creating, or changing a Pixi workspace, including manifests, dependencies, platforms, targets, features, environments, tasks, lockfiles, editable Python…

    100 GitHub stars~1.3k tokensUpdated today
    Auto-check passed

Works with

Questions about Auv Wayland Rendering

What does Auv Wayland Rendering do?

Prepare, diagnose, and validate Linux GPU and Wayland environments for AUV rendering and capture through XDG Desktop Portal and PipeWire. Auv Wayland Rendering is an agent skill from moeru-ai/auv. Prepare, diagnose, and validate Linux GPU and Wayland environments for AUV rendering and capture through XDG Desktop Portal and PipeWire.

When should I use Auv Wayland Rendering?

Auv Wayland Rendering fits situations like: installing AUV desktop runtime dependencies; connecting from another machine over SSH; using an existing compositor; A headless wlroots/Sway session.

How do I install Auv Wayland Rendering in Claude Code?

Run `npx skills add moeru-ai/auv --skill auv-wayland-rendering -a claude-code`. Or copy the skill folder (.agents/skills/auv-wayland-rendering in moeru-ai/auv) into .claude/skills/auv-wayland-rendering in your project. Claude Code loads it when a task matches its description.

How do I install Auv Wayland Rendering in Codex?

Run `npx skills add moeru-ai/auv --skill auv-wayland-rendering -a codex`. Or copy the skill folder (.agents/skills/auv-wayland-rendering in moeru-ai/auv) into .agents/skills/auv-wayland-rendering in your project. Codex loads it when a task matches its description.

Can I use Auv Wayland Rendering 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 moeru-ai/auv --skill auv-wayland-rendering -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auv-wayland-rendering, .gemini/skills/auv-wayland-rendering, .github/skills/auv-wayland-rendering and .opencode/skills/auv-wayland-rendering in your project.

What does Auv Wayland Rendering need to run?

Going by SKILL.md and its folder, Auv Wayland Rendering needs a shell for the scripts in its folder and the command-line tools its instructions call (cargo). Our summary lists: A Bash shell.

Does Auv Wayland Rendering access the network?

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.

Is Auv Wayland Rendering 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Auv Wayland Rendering use?

Auv Wayland Rendering is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Auv Wayland Rendering use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 2.7k tokens, read only when the agent opens those files.

What are the alternatives to Auv Wayland Rendering?

Skills that share tags, products or a category with Auv Wayland Rendering: Cloud Computer Use (davidondrej/cloudroom-core, 285 stars), Gui Onboarding Verification Skill (warpdotdev/warp, 65k stars), Daily Update (Ar9av/obsidian-wiki, 3.5k stars) and Eradicating Malware From Infected Systems (mukul975/Anthropic-Cybersecurity-Skills, 34k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Auv Wayland Rendering?

moeru-ai (a GitHub organization) maintains it in moeru-ai/auv, which has 100 GitHub stars. The repository was last updated on October 11, 2026.

Source: moeru-ai/auv on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.