A reference guide for the vx command-line tool, including commands, flags, output formats, and fields returned by project-analysis commands. JSON is a structured format that is easy for programs and agents to read.

Use it when checking project requirements, analysing its structure, generating AI context, or looking up vx command syntax.

It reduces guesswork when using vx and helps produce consistent machine-readable output. It also explains what project-analysis results contain.

How loonghao/rez-next configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to loonghao/rez-next. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/loonghao/rez-next/main/.agents/skills/vx-commands/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/loonghao/rez-next

Made for: Claude Code, Codex.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/loonghao/rez-next/vx-commands.svg)](https://agentmods.dev/skills/loonghao/rez-next/vx-commands)

Your own site

<a href="https://agentmods.dev/skills/loonghao/rez-next/vx-commands"><img src="https://agentmods.dev/badge/skills/loonghao/rez-next/vx-commands.svg" alt="Measured on agentmods" height="20"></a>

Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,445 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00043	$0.01445
Opus 5	$0.00022	$0.00723
Sonnet 5	$0.00009	$0.00289
Haiku 4.5	$0.00004	$0.00145

Measured 6d ago against content hash c416a6bc7fdb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

vx-commands 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 6d 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.

.agents/skills/vx-commands/SKILL.md · 210 lines

How it starts

The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.

VX Command Reference

Quick rule: All vx commands support --json for structured output and --format toon for token-optimized output (saves 40-60% tokens). Set VX_OUTPUT=json to default all commands to JSON.

Structured Output Commands (AI-Optimized)

All commands support --json for structured output and --format toon for token-optimized output (saves 40-60% tokens).

Project Analysis

vx analyze --json           # Analyze project structure
vx check --json             # Verify tool constraints
vx ai context --json        # Generate AI-friendly project context

Output fields (analyze):

ecosystems[] - Detected ecosystems (nodejs, python, rust, go)
dependencies[] - Project dependencies
scripts[] - Available scripts
required_tools[] - Tools needed

Output fields (check):

requirements[] - Tool requirement status
all_satisfied - Whether all constraints are met
missing_tools[] - Tools that need installation

Output fields (ai context):

project - Project info (name, languages, frameworks)
tools[] - Installed tools with versions
scripts[] - Available scripts
constraints[] - Tool constraints

Tool Management

vx list --json              # List installed tools
vx versions node --json     # List available versions
vx which node --json        # Find tool location
vx search <query> --json    # Search for tools

Output fields (list):

runtimes[] - Available runtimes
total - Total count
installed_count - Installed count

Output fields (versions):

versions[] - Available versions with metadata
latest - Latest version
lts - LTS version (if applicable)

Output fields (which):

path - Executable path
version - Resolved version
source - Source (vx, system, global_package)

Installation

vx install node@22 --json   # Install tool
vx sync --json              # Sync from vx.toml

Output fields (install):

runtime - Tool name
version - Installed version
path - Installation path
duration_ms - Installation duration
dependencies_installed[] - Dependencies also installed

Read the full file on GitHub · 210 lines

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.

6d ago First seen · 210 lines · 43 tokens per session scan A c416a6bc7fdb

Subscribe to this mod's changes

vx-commands is a skill published in the GitHub repository loonghao/rez-next (25 stars, last pushed 2d ago), licensed Apache-2.0. It adds 43 tokens to every session and 1,445 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 2026-09-02.

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