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BC auditcore-network-audit

AuditCore — Suite completa de auditoría de seguridad para infraestructura de red. Cubre 6 vendors (F5, Cisco, Fortinet, Palo Alto, Juniper, Arista), 5 frameworks (NIST 800-53, NIST CSF 2.0, CIS Controls v8, PCI DSS v4.0, ISO 27001:2022), generación automática de scripts de remediación con rollback, reportes HTML ejecutivos y técnicos, y diagnóstico de salud de infraestructura. Arquitectura en capas (Layer 0→1→2→3) optimizada para ventanas de contexto reducidas.

ClawHub Agent Skills author: santanallen v1.0.0 MIT-0 25 files body ≈ 1 309 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

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

AnalyzerInfrastructureData and analyticstype 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
B
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security skill-card.md:22
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    Risk: The community index and local tools inventory can route the agent toward broader offensive security tooling. <br>

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

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 53/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 20When it triggers. No condition that starts the skill
  • 100Tools and files. No external tools needed
  • 100Steps. 7 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1309 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 465: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 7 items
  • +4Has examples (6 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: suspicious
This is a mostly coherent network-audit suite, but it under-labels write, persistence, script-generation, and broad offensive-tool routing behavior as read-only.
LLM: suspicious (high) · VirusTotal: · 29 May 2026