Skillguard

SkillGuard

SkillGuard is a local-first security scanner and policy gate for Agent Skills. It is designed to run before a third-party skill is installed.

SkillGuard is not a certification system. It is a deterministic lint and policy engine for catching high-risk skill behavior before installation.

Status: alpha. The scanner is useful as a local install gate and CI signal, but it does not prove that a skill is safe.

Goals

• Scan skill directories without executing skill code.
• Work offline by default.
• Produce stable JSON and SARIF reports for installers and CI.
• Keep the scanner generic while allowing products to enforce stricter policy.
• Stay Bun-first at the CLI and portable TypeScript in the core.

Quick Start

bunx @stll/skillguard scan ./skill --preset strict --policy strict

Scan a local directory, zip file, Git URL, or direct URL. Remote inputs require explicit network opt-in:

bunx @stll/skillguard scan https://github.com/org/skill --allow-network

Try the repository fixtures from a clone:

bun install
bun --filter @stll/skillguard skillguard scan ./fixtures/malicious

JSON output:

bunx @stll/skillguard scan ./skill \
  --preset strict \
  --policy strict \
  --format json

Markdown output:

bunx @stll/skillguard scan ./skill \
  --format markdown \
  --output skillguard-report.md

SARIF output:

bunx @stll/skillguard scan ./skill --format sarif --output skillguard.sarif

Presets

--preset controls scan breadth. --policy controls which severities fail the install gate. Keep these knobs separate: a broad scan can still use an advisory policy, and a quick scan can still fail on medium findings.

| Preset | Purpose | | --- | --- | | quick | High-confidence local checks for install gating. | | standard | Default. Adds dependency hygiene, dangerous code, taint-flow, and output-handling checks. | | strict | Adds lower-confidence behavioral checks: excessive agency, memory poisoning, tool misuse, trigger abuse, and MCP/tool metadata poisoning. | | paranoid | Adds malware/offensive-tool indicators, generic network-use findings, offline dependency advisory fallback, and OSV lookup when --allow-network is set. |

Examples:

skillguard scan ./skill --preset quick --policy standard
skillguard scan ./skill.zip --preset strict --policy strict
skillguard scan https://github.com/org/skill --preset paranoid --allow-network

Semantic Review

Semantic review is optional and off by default. It sends a bounded, redacted review packet for the candidate skill to an OpenAI-compatible model provider and turns the response into normal SkillGuard findings under skillguard.semantic-review.

It requires explicit network opt-in:

skillguard scan ./skill \
  --preset paranoid \
  --policy strict \
  --allow-network \
  --semantic \
  --semantic-provider openai

Configuration:

• OPENAI_API_KEY or SKILLGUARD_SEMANTIC_API_KEY
• SKILLGUARD_SEMANTIC_MODEL or --semantic-model
• OPENAI_BASE_URL, SKILLGUARD_SEMANTIC_BASE_URL, or

--semantic-base-url for OpenAI-compatible endpoints

Do not run semantic review on broad workspace roots containing unrelated user documents or secrets. Scan only the third-party skill package being evaluated.

Packages

• @stll/skillguard-core: traversal, report types, policy evaluation, rule runtime.
• @stll/skillguard-rules: built-in deterministic rules.
• @stll/skillguard-sarif: SARIF 2.1.0 report conversion.
• @stll/skillguard: Bun-first CLI and TanStack Intent skill.

The @stll/skillguard package also ships a TanStack Intent skill at skills/security-scan/SKILL.md, so agents that discover package-provided skills can invoke SkillGuard before installing third-party skills.

Public Rule Catalog

@stll/skillguard-rules exports RULE_CATALOG, a documented catalog of 64 stable pattern IDs across the built-in rule set. Findings include these IDs in finding.metadata.pattern when a specific pattern matched, so installers and CI can suppress, explain, or route findings without depending only on prose.

Security Defaults

• No skill code execution.
• No network calls unless --allow-network is set.
• No symlink following.
• File count, file size, total byte, and depth limits.
• Text scanning only; binary files are fingerprinted and skipped.
• Package install scripts are flagged.
• Remote Git/URL inputs require --allow-network.
• Local zip extraction blocks zip-slip paths.

Current Analyzer Coverage

SkillGuard is inspired by NVIDIA's Python-based SkillSpector, but it is not a line-for-line port. It implements the same install-gate classes where they make sense for a Bun-first scanner:

• prompt injection and hidden instructions;
• system prompt leakage;
• harmful content;
• data exfiltration and secret access;
• privilege escalation;
• supply-chain risk, package lifecycle scripts, dependency hygiene, npm/PyPI

lockfile discovery, offline advisory fallback, and optional OSV;

• dangerous Python/JavaScript/TypeScript/shell execution constructs;
• source-to-sink taint-flow heuristics, including structured intra-file

assignment tracking for Python and JavaScript/TypeScript;

• output handling;
• excessive agency;
• memory poisoning;
• rogue-agent persistence and self-modification;
• trigger abuse;
• MCP least-privilege and tool metadata poisoning;
• malware/offensive-tool indicators.

The intentionally deferred piece is native YARA rule execution. Provider-backed semantic analysis exists, but it is explicit opt-in because it sends candidate skill content to a model provider.

AST Analysis

AST means "abstract syntax tree": the scanner parses source into a syntax tree and inspects the structure of the code without running it. That catches behavior that plain text matching can miss, for example exec(requests.get(...)), subprocess.run(...), eval(await fetch(...)), or aliased child_process.exec(...) calls even if spacing or formatting changes.

SkillGuard uses TypeScript-native parsers for Python and JavaScript/TypeScript analysis, so the Bun-first package does not require language runtimes to be installed and does not execute candidate skill code.

Fixtures

The fixtures/ corpus includes benign, malicious, and evasive skills used by the regression tests. The benign fixture is expected to stay quiet for high-risk findings; malicious and evasive fixtures cover install hooks, secret/file exfiltration, Python and JavaScript/TypeScript taint flow, encoded execution, and hidden Unicode.

CI

See [docs/github-action.md](docs/github-action.md) for strict-gate and SARIF upload examples.

See [docs/release.md](docs/release.md) for the npm publish order and release verification checklist.

Development

bun install
bun run lint:ws
bun run typecheck
bun run lint
bun run format:check
bun run test
bun run knip
bun run build
bun --filter @stll/skillguard intent:validate
bun run pack:verify

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: stella
• Source: stella/skillguard
• License: Apache-2.0
• Homepage: https://stll.app

Install and usage instructions live in the source repository linked above.