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How to scan an agent skill for prompt injection and exfiltration before installing with Skill Spector

Run Skill Spector on a skill directory or repo and read its risk score and findings first.

Short answer: Install with uv tool install git+https://github.com/NVIDIA/skillspector.git; then download or clone the skill you want to check; Scan it without LLM costs using Docker: docker run --rm -v "$PWD:/scan" skillspector scan ./my-skill/ --no-llm. All steps.

Who it is forA developer about to install a community skill into Claude Code or Codex.

The problemSkills run with implicit trust; the README cites research where 26.1% of analyzed skills had vulnerabilities and 5.2% showed likely malicious intent.

The outcomeA 0 to 100 risk score with severity labels and findings, so you decide whether to install.

What you need first

  • Python with uv or pip, or Docker (no Python required)
  • Optional: an LLM API key in .env for semantic analysis (default config targets DeepSeek)
  • Optional MCP extra for skillspector mcp

Steps

  1. Install with uv tool install git+https://github.com/NVIDIA/skillspector.git
  2. Download or clone the skill you want to check
  3. Scan it without LLM costs using Docker: docker run --rm -v "$PWD:/scan" skillspector scan ./my-skill/ --no-llm
  4. Read the risk score, severity labels and recommendations
  5. Install the skill only if the findings are acceptable

Prompt for your agent

Use NVIDIA/SkillSpector to scan the skill at <path or repo> before I install it. Run static analysis only, then summarize the risk score and each finding in plain words, and recommend install, review or reject.

Caveat. A clean scan lowers risk but is not a guarantee; static analysis cannot prove a skill is safe.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for NVIDIA/SkillSpector and "Scan an agent skill for prompt injection and exfiltration before installing"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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