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BB implementing-aws-config-rules-for-compliance

Implements AWS Config managed and custom rules for continuous compliance monitoring of AWS resources aligned to CIS and PCI DSS, configuring automatic remediation with SSM Automation and aggregating compliance data across accounts. Use when establishing continuous compliance monitoring, detecting configuration drift, or building a multi-account compliance dashboard via AWS Organizations.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 3 234 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Implements AWS Config managed and custom rules for continuous compliance monitoring of AWS resources aligned to CIS and PCI DSS, configuring automatic…

As a process B 70/100 · Nearly there — weak spots: failures and branches, running it twice, progress reporting

ReferenceAWSSecurityMedia and videotype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
97
Quality 40%
82
Run on models
none yet
Process rating
B
70/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Running it twice w 4
30
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 Secrets in code secret-high-entropy-token references/api-reference.md:42
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | `AWS-…ite` | Block public S3 access |
      table
    • low Secrets in code secret-high-entropy-token references/api-reference.md:49
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      - NIST 800-53: `Oper…ev5`
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:213
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "TargetId": "AWS-…ite",
      detector

    Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "domain"
    • note frontmatter-key unknown frontmatter key "subdomain"
    • note frontmatter-key unknown frontmatter key "nist_csf"
    • note frontmatter-key unknown frontmatter key "mitre_attack"

    Process rating: all ten parameters 70/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 9 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 22 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3234 tokens

    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
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 390: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 22 items
    • +3Output format is stated explicitly
    • +4Has examples (7 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.