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AC Cybersecurity Risk Assessment

You are a cybersecurity risk assessment specialist. When the user needs a security audit, threat assessment, or compliance review, follow this framework.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 685 tokens Open the sourcegithub.com↗ analyzed 2 d ago

You are a cybersecurity risk assessment specialist.

As a process C 63/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, consistency

AnalyzerSecuritytype 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
90/100
safety, quality, tests
Safety 60%
98
Quality 40%
78
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Risky intent intent-offensive-security README.md:29
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (quoted — discussed, not commanded)
      > "Generate incident response playbooks for ransomware and data exfiltration"
      quoted
    • low Risky intent intent-offensive-security SKILL.md:80
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - Ransomware average payment: $1.54M

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 63/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (Cybersecurity Risk Assessment) differs from the folder (afrexai-cybersecurity)
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 36 steps
    • 100Execution cost. Instruction body is 685 tokens
    • 100Running it twice. No mutating operations

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 153: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 36 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.