SKILLEMALL.ai
GitHub ↗ RU Sign in

AC security-scanner

Comprehensive vulnerability and malware scanner for skills and code. Detects code execution vulnerabilities (eval, exec, dynamic require), credential theft patterns, network calls to suspicious domains, obfuscation, and more. Provides risk assessment (SAFE/CAUTION/DANGEROUS) with detailed findings and actionable recommendations. Use before installing untrusted skills or when reviewing code for security issues.

modbender/skill-library-mcp Agent Skills author: modbender MIT 9 files · 2 scripts body ≈ 2 341 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Comprehensive vulnerability and malware scanner for skills and code.

As a process C 53/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, consistency

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
53/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: skill-library-mcp, skill-library-mcp

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 53/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (security-scanner) differs from the folder (security-scanner-skill)
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 66 steps, 3 vague phrases
    • 100Execution cost. Instruction body is 2341 tokens
    • 100Running it twice. Mutating operations check current state
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 13 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -221 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +3Description length 413: enough signal without eating the budget
    • +4Structure: 38 headings
    • +3Step-by-step instructions: 66 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.