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BC vaikora-security

Route OpenClaw LLM calls through Vaikora for real-time AI agent security monitoring. Every action your agent takes gets scored for risk, anomaly-flagged, and pushed as a security signal to SentinelOne, CrowdStrike, or AWS Security Hub, without changing how your agent works.

ClawHub Agent Skills author: Data443 v1.0.1 MIT-0 2 files body ≈ 1 571 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

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

ProcedureAWSAI and agentsInfrastructuretype 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
When it triggers w 12
20
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 Exfiltration net-credential-use SKILL.md:119
    Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
    curl -H "x-api-key: ${VAIKORA_API_KEY}" \
    security skill

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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 7 mutating operations with no state check
  • 40Consistency. Frontmatter name (vaikora-security) differs from the folder (vaikora)
  • 55Failures and branches. 1 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 25 steps
  • 100Execution cost. Instruction body is 1571 tokens
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 10 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 274: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 25 items
  • +4Has examples (4 code blocks)

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

External checks

ClawHub: clean
This is a disclosed LLM security proxy skill that intentionally routes model traffic and provider credentials through Vaikora, so it is sensitive but coherent with its stated purpose.
LLM: benign (high) · VirusTotal: suspicious · 28 May 2026