virtualization-framework-workflow

virtualization-framework-workflow is a skill for Claude Code, Codex from gaelic-ghost/socket. It costs 49 tokens per session (898 once invoked), scanned A, original, Apache-2.0.

A workflow for building custom virtual machines with Apple's Virtualization framework on macOS or Linux. A virtual machine runs another operating system inside a host app.

In plain words
What is it for?
Use it to create or diagnose a custom VM host, configure macOS or Linux guests, manage VM bundles, handle save and restore checks, and connect a VM to a user interface.
Why use it?
It keeps guest operating-system differences, boot settings, device setup, saved state, permissions, and lifecycle handling explicit.

Skill for Claude CodeCodex

Part of the apple-dev-skills plugin — 65 skills, 2 MCP servers shipped together

Install

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.

agentmods
npx agentmods add skills/gaelic-ghost/socket/virtualization-framework-workflow
Any agent
npx skills add gaelic-ghost/socket --skill virtualization-framework-workflow
Clone the repo
git clone --depth 1 https://github.com/gaelic-ghost/socket

Made for: Claude Code, Codex.

Or install apple-dev-skills, the plugin that ships this one along with the rest of its 65 skills, 2 MCP servers.

Wrote 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.

agentmods badge for virtualization-framework-workflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/gaelic-ghost/socket/virtualization-framework-workflow.svg)](https://agentmods.dev/skills/gaelic-ghost/socket/virtualization-framework-workflow)
Your own site
<a href="https://agentmods.dev/skills/gaelic-ghost/socket/virtualization-framework-workflow"><img src="https://agentmods.dev/badge/skills/gaelic-ghost/socket/virtualization-framework-workflow.svg" alt="Measured on agentmods" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 898 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00049 $0.00898
Opus 5 $0.00024 $0.00449
Sonnet 5 $0.00010 $0.00180
Haiku 4.5 $0.00005 $0.00090

Measured yesterday against content hash 9b35a9affb3c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

virtualization-framework-workflow 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 yesterday.

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.

plugins/apple-dev-skills/skills/virtualization-framework-workflow/SKILL.md · 69 lines

How it starts

The opening of the file, as written. The whole thing — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Virtualization Framework Workflow

Purpose

Implement one explicit macOS or Linux Virtualization framework path without flattening their platform, boot, identity, or device differences.

When To Use

  • Use for VZVirtualMachineConfiguration, guest devices, VZVirtualMachine, VZVirtualMachineView, lifecycle, and diagnostics.
  • Use when building a custom VM host app or Swift package rather than operating an existing VM manager.
  • Use for save/restore capability checks, not as a general snapshot-product workflow.

Single-Path Workflow

  1. Read current Xcode-local Virtualization documentation for every selected API and availability gate.
  2. Consume or create the virtualization shape record.
  3. Choose the guest family using macOS and Linux guest matrix:
    • macOS: Mac platform identity, macOS boot loader, restore-image compatibility, auxiliary storage
    • Linux/generic: generic platform, Linux or EFI boot, kernel/initrd/command line or EFI disk
  4. Separate the implementation into configuration construction, bundle/artifact persistence, VM lifecycle, and optional UI ownership. Make a headless console/service path or VZVirtualMachineView ownership explicit rather than creating both accidentally.
  5. Add only required devices after checking device and availability matrix.
  6. Require the virtualization entitlement, supported CPU/memory values, exact OS availability, and validate() before start.
  7. Model start, pause, resume, stop, and state transitions explicitly. Save/restore only in documented states with a configuration compatible with the saved state.
  8. Validate configuration, boot, console/UI, disk, network, shares, services, shutdown, and teardown at the narrowest relevant level.
  9. Preserve the failed configuration surface, VM state, host/guest versions, underlying error, and likely cause.

Read the full file on GitHub · 69 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. yesterday First seen · 69 lines · 49 tokens per session scan A 9b35a9affb3c

Subscribe to this mod's changes

virtualization-framework-workflow is a skill published in the GitHub repository gaelic-ghost/socket (7 stars, last pushed 9d ago), licensed Apache-2.0. It adds 49 tokens to every session and 898 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

pipeline

Use when the user wants a feature idea taken end-to-end in one autonomous run — phrases like "run the whole pipeline", "take this feature from idea to finished branch", "brainstorm then build it autonomously", "do everything from idea to merged", "implement all phases without stopping". Triggers when they want…

kardebadas/claude-plugin · 80 tokens

craft

Use when a product idea is still vague and needs to become a clear definition of what to build — "let's craft an app like X", "help me define what I actually want", "clarify this idea before we plan it". Also use before planning or implementation when requirements, UX, domain behaviour, or technical preferences have…

kardebadas/claude-plugin · 83 tokens

scenario-planning

Plans under genuine uncertainty — building scenarios, identifying which assumptions are load-bearing, setting early-warning indicators, and stress-testing a plan against futures rather than forecasting one. Use this when a decision depends on something unknowable, when a plan assumes conditions that may not hold…

cbrock84/headcount · 78 tokens

ai-ml-governance

Governs models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory…

cbrock84/headcount · 83 tokens

ai-research-analyst

Produces executive-level research — market sizing, competitor mapping, trend analysis, and strategic intelligence — grounded in cited sources with the confidence in each claim made explicit. Use this to analyze a market or industry, map competitors, evaluate a market-entry or build-versus-buy decision, produce a…

cbrock84/headcount · 91 tokens

implement-factory

Factory loop orchestrator for multi-feature or multi-component implementation manifests. Use for high-complexity work with parallel-eligible workstreams and holdout-scenario evaluation.

rsmdt/the-startup · 37 tokens