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AB setup-security-agent

Configure AWS Security Agent for the current workspace — provision or reuse an agent space, IAM service role, and S3 bucket. Use when the user asks to "set up security agent", "configure security scanner", "is security agent configured", or on first-time use before any scan or pentest.

ClawHub Agent Skills author: Amazon Web Services 1 file body ≈ 2 010 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Configure AWS Security Agent for the current workspace — provision or reuse an agent space, IAM service role, and S3 bucket.

As a process B 71/100 · Nearly there — weak spots: result and completion, inputs and preconditions

ProcedureAWSAI and agentstype 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%
97
Quality 40%
89
Run on models
none yet
Process rating
B
71/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • low Risky intent intent-offensive-security SKILL.md:3
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      description: Configure AWS Security Agent for the current workspace — provision or reuse an agent space, IAM service role, and S3 bucket. Use when the user asks to "set up security agent", "configure
      detector
    • low Risky intent intent-offensive-security SKILL.md:18
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
      - `pentests.json` — same shape, for pentest jobs
    • low Risky intent intent-offensive-security SKILL.md:171
      Offensive-security / dual-use content (legitimate for authorised testing; review intended use) (detector / deny-list definition)
      - The scan and pentest skills can call this skill inline if `config.json` is missing — first-time users don't need to run setup separately.
      detector

    Files scanned: 1. 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 71/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 32 steps
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2010 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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

    • +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
    • +5Description quotes 3 example trigger phrases
    • +3Description length 286: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 32 items
    • +4Has examples (13 code blocks)

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