SKILLEMALL.ai

CC implementing-aws-nitro-enclave-security

Build AWS Nitro Enclave confidential computing environments using nitro-cli to create enclave images, configure attestation-aware KMS policies with PCR condition keys, validate attestation documents against the Nitro PKI root, and set up vsock/kmstool-enclave-cli pipelines for processing PII, keys, and health records. Use for Nitro Enclave setup, attestation validation, or scoping KMS to an enclave image hash.

mukul975/Anthropic-Cybersecurity-Skills Agent Skills author: mukul975 Apache-2.0 4 files · 1 script body ≈ 5 252 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Build AWS Nitro Enclave confidential computing environments using nitro-cli to create enclave images, configure attestation-aware KMS policies with PCR…

As a process C 61/100 · Has gaps — weak spots: failures and branches, running it twice, progress reporting

IntegrationAWSDockerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
72
Run on models
none yet
Process rating
C
61/100
Has gaps
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

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 Dangerous commands cmd-background-process SKILL.md:66
    Starts a background / autostarted process (documentation of a security skill)
    sudo systemctl enable --now nitro-enclaves-allocator.service
    security skill
  • low Dangerous commands cmd-background-process SKILL.md:67
    Starts a background / autostarted process (documentation of a security skill)
    sudo systemctl enable --now docker
    security skill

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5252 tokens (recommended < 5000); move details to references/
  • 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 61/100

  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 10 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5252 tokens
  • 100Steps. 69 steps
  • 100Consistency. Name and required fields are in place

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 413: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 69 items
  • +3Output format is stated explicitly
  • +4Has examples (17 code blocks)
  • +1License stated

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