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.
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
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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-processSKILL.md:66Starts a background / autostarted process (documentation of a security skill)sudo systemctl enable --now nitro-enclaves-allocator.service
security skill -
low Dangerous commands
cmd-background-processSKILL.md:67Starts 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-longSKILL.md body ≈ 5252 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "domain" - note
frontmatter-keyunknown frontmatter key "subdomain" - note
frontmatter-keyunknown frontmatter key "nist_csf" - note
frontmatter-keyunknown 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.