Skill Auditor in Sandbox

Launch a NovitaClaw (OpenClaw) sandbox, install a specified skill, and generate an installation & security audit report. Use when: (1) You want to test a community skill before installing it locally, (2) You need a security audit of a skill's code, hooks, and dependencies, (3) You want to verify a skill from ClawHub or GitHub in an isolated environment.

Test and audit Claude Code skills in an isolated NovitaClaw (OpenClaw) sandbox before installing them locally. The skill launches a sandbox, installs the target skill, runs a security scan, and generates a structured risk report.

Quick Reference

Situation	Action
Test a ClawHub skill	/skill-auditor-in-sandbox owner/skill-name
Test a GitHub skill	/skill-auditor-in-sandbox owner/repo-name
Review the report	Check risk level, suspicious patterns, URLs, external paths
After review	Pause or stop the sandbox to save costs

Prerequisites

• NOVITA_API_KEY must be set. If not, ask the user to register at https://novita.ai/?utm_source=OpenClaw&utm_medium=Dev_Rel&utm_campaign=Claw-30 and get an API key from https://novita.ai/settings/key-management, then: export NOVITA_API_KEY=<key>
• novitaclaw CLI must be installed. If not found: curl -fsSL https://novitaclaw.novita.ai/install.sh | bash
• novita-sandbox npm package must be available. If not: npm install novita-sandbox

Usage

You are given a skill name (or identifier) as $ARGUMENTS. Your job is to launch a sandbox, install the skill, run a security audit, and generate a report.

Step 1: Launch Sandbox

bash

novitaclaw launch --json

Parse the JSON output and extract sandbox_id and webui. Save these for the report.

If launch fails, check error_code and remediation fields:

• MISSING_API_KEY → ask user for API key
• SANDBOX_TIMEOUT → retry with --timeout 300

Step 2: Install Skill

Run the install script from the project root:

bash

SANDBOX_ID=<sandbox_id> SKILL_NAME="$ARGUMENTS" node scripts/install-skill.mjs

The script outputs JSON: { success, method, skillDir, files, error? }.

• If success is false, show the error and stop.
• Note the method used (clawhub / git-github / git-clawhub) for the report.

Step 3: Security Audit

Run the audit script:

bash

SANDBOX_ID=<sandbox_id> SKILL_NAME="$ARGUMENTS" node scripts/audit-skill.mjs

The script outputs JSON:

• suspicious[] — lines matching risky code patterns (dynamic execution, shell spawning, encoding, etc.)
• urls[] — all URL references found in skill files
• externalPaths[] — references to paths outside the skill directory (system dirs, dotfiles, temp dirs)
• dependencies — contents of requirements.txt or package.json if present
• fileContents[] — full contents of all text files for manual review

Step 4: Assess Risk

Based on audit results, assign a risk level:

Risk Level	Criteria
LOW	No suspicious patterns, URLs are legitimate (GitHub, docs), no external paths
MEDIUM	Some suspicious patterns but explainable (e.g., fetch() for legitimate API calls)
HIGH	Unexplained network calls, access to sensitive paths, obfuscated code
CRITICAL	Credential harvesting, mining indicators, command injection patterns

Step 5: Generate Report

Output a structured report:

text

## Skill Installation Report

**Skill:** <skill-name>
**Sandbox ID:** <sandbox_id>
**Web UI:** <webui_url>
**Timestamp:** <current time>

### Installation Status
- **Result:** SUCCESS / FAILED
- **Method:** <clawhub / git-github / git-clawhub>
- **Files Installed:** <count> files

### Installed Files
<table of files and their purpose>

### Security Analysis
- **Risk Level:** LOW / MEDIUM / HIGH / CRITICAL

### Suspicious Patterns Found
| File | Line | Pattern | Severity |
|------|------|---------|----------|
(or "None found")

### URL References
| File | URL | Context |
|------|-----|---------|
(list all URLs and whether they look legitimate)

### External Path References
(list any, or "None found")

### Dependencies
(list any, or "No external dependencies")

### Recommendations
- <recommendation based on findings>

### Sandbox Management
- To access: <webui_url>
- To pause (save costs): `novitaclaw pause <sandbox_id>`
- To stop (permanent): `novitaclaw stop <sandbox_id>`

After generating the report, automatically pause the sandbox to save costs:

bash

novitaclaw pause <sandbox_id> --json

Then inform the user that the sandbox has been paused and can be resumed or stopped:

• To resume: novitaclaw resume <sandbox_id>
• To stop (permanent): novitaclaw stop <sandbox_id>

What Gets Scanned

Category	Patterns
Suspicious code	Shell spawning, dynamic code execution, encoding functions, mining indicators
Network calls	All URL references found in skill files
External paths	System directories, user home dotfiles, temp directories
Dependencies	requirements.txt, package.json
File contents	Full text of all .md, .txt, .json, .py, .js, .ts, .sh, .yaml, .yml files

Important Notes

• Always use --json flag with novitaclaw commands.
• The sandbox auto-terminates based on keep_alive. Suggest pause to save costs.
• Prefer pause over stop — stop is irreversible. Confirm before stopping.

Attribution

• Source: https://github.com/freecodewu/skill-auditor-in-sandbox
• Powered by NovitaClaw sandbox infrastructure