CD configuring-microsegmentation-for-zero-trust
Configures microsegmentation policies to enforce least-privilege workload-to-workload access using tools such as VMware NSX, Illumio, and Calico, preventing lateral movement in zero trust architectures. Use when designing or implementing network microsegmentation as part of a zero trust architecture aligned with NIST SP 800-207.
Configures microsegmentation policies to enforce least-privilege workload-to-workload access using tools such as VMware NSX, Illumio, and Calico, preventing…
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, failures and branches
How to improve
- 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 · 4
✓ No critical or high findings
Medium and low: 4
-
low Risky intent
intent-offensive-securityassets/template.md:69Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- [ ] Lateral movement from compromised workload is contained
-
low Risky intent
intent-offensive-securitySKILL.md:42Offensive-security / dual-use content (legitimate for authorised testing; review intended use)Microsegmentation divides a network into granular security zones, enforcing least-privilege access between workloads at the application layer rather than relying on traditional VLAN-based segmentation
-
low Risky intent
intent-offensive-securitySKILL.md:147Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- Run penetration tests attempting lateral movement between segments
-
low Risky intent
intent-offensive-securitySKILL.md:168Offensive-security / dual-use content (legitimate for authorised testing; review intended use)- [ ] Lateral movement tests confirm blocked unauthorized traffic
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- 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 49/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 7 mutating operations with no state check
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 74 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1798 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -43 reference files, but SKILL.md never points to them: the model will not open them
- -32 of 2 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 330: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (1 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.