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AB nist-compliance-assessment

NIST Cybersecurity Framework (CSF) and SP 800-53 Rev 5 compliance assessment for network infrastructure. Maps device configuration against 6 control families with direct network device relevance — Access Control (AC), Audit and Accountability (AU), Configuration Management (CM), Identification and Authentication (IA), System and Communications Protection (SC), and System and Information Integrity (SI). Focuses on CSF Protect (PR) and Detect (DE) functions for network security posture assessment.

ClawHub Agent Skills author: Vahagn Madatyan v1.0.0 MIT-0 4 files body ≈ 4 833 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 77/100 · Nearly there — weak spots: result and completion, when it triggers

AnalyzerInfrastructureSecuritytype 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%
98
Quality 40%
89
Run on models
none yet
Process rating
B
77/100
Nearly there
When it triggers w 12
20
Result and completion w 14
40
Inputs and preconditions w 11
70
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 references/control-reference.md:30
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      | AU-2 | Event Logging | DE.AE | Verify logging captures login attempts, config changes, ACL matches, privilege escalation | ✓ | ✓ | ✓ |
      detector
    • low Risky intent intent-offensive-security SKILL.md:147
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      including login attempts, configuration changes, privilege escalation,

    Files scanned: 4. 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 77/100

    • 20When it triggers. No condition that starts the skill
    • 40Result and completion. Does not say what the result is
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4833 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 21 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 500: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    External checks

    ClawHub: clean
    This is a read-only NIST network compliance checklist; it can expose sensitive device configuration data, but that matches its stated audit purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026