Skillxray
Scan an AI agent skill for prompt injection, hidden Unicode, dangerous commands, and leaked secrets before you install it.
npx -y skills add munzzyy/skillxray --skill skillxrayAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 26 days oldThe repository was created 26 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Scan an AI agent skill, plugin, or MCP bundle for security and hygiene problems before installing or trusting it - prompt injection in the instructions, hidden/invisible Unicode, dangerous commands (curl-pipe-sh, reverse shells), data exfiltration, hardcoded secrets, and auto-running hooks. Use before adding a third-party skill or plugin, before wiring up an MCP server someone else wrote, or whenever you're about to trust a SKILL.md you didn't write. Returns an A-F grade and a per-finding report.
SKILL.md
2.6 KB, 536 tokens by cl100k_base, as published. Nobody here has run it
skillxray
Run this before you install or trust an AI agent skill you didn't write - a SKILL.md, a Claude Code plugin, an MCP bundle, or a whole directory of them. It reads the files and flags what a quick glance would miss: instructions aimed at the agent instead of the user, invisible Unicode, curl-pipe-sh and reverse shells, exfiltration to an outside host, leaked keys, and hooks that run on their own. It tells you what's wrong and where; it doesn't fix it for you.
When to use it
Before:
- installing a third-party skill, plugin, or MCP server someone else wrote
- trusting a
SKILL.mdpulled from a repo or a registry - adding a skill bundle to a shared or automated environment
Run it and read the findings before the skill is live, not after.
How to run it
Point it at a skill directory, a single SKILL.md, or a directory of skills:
skillxray <path> --json
<path> defaults to the current directory. To vet something you haven't
cloned yet, let skillxray do the shallow read-only clone itself:
skillxray --git https://github.com/owner/some-skill --ref main --json
--json gives machine-readable output; --sarif emits SARIF 2.1.0 for the
GitHub Security tab; leave both off for the colored human report. --quiet
prints just the summary line and grade.
Reading the result
Every scan ends in a letter grade, A through F. Any critical finding drops it straight to F; high-severity findings cap it below an A. The grade is the five-second read; the findings under it are the reason.
The exit code is what to gate on in CI or a script: skillxray exits non-zero
when any finding lands at or above --fail-on (critical|high|medium|low|info|none,
default high). So a default run passes on low/medium hygiene notes and fails
on the things that actually get you owned.
A clean grade means skillxray didn't find one of the patterns it checks for, not that the skill is safe to run blind. Read what it flagged, and for anything it grades below an A, understand the specific finding before you decide to trust the skill anyway - the report names the rule and the line so you can go look.