This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user asks to "analyze Terraform modules", "scan IaC for security issues", "review Terraform configurations", "check infrastructure code for misconfigurations", or "audit cloud resources".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Category: Engineering Domain: Infrastructure as Code
The Terraform Patterns skill provides automated analysis of Terraform configurations for module complexity, security misconfigurations, and infrastructure best practices. It catches open ports, public buckets, missing encryption, and overly permissive IAM policies before they reach production.
Before analyzing or scanning, confirm these inputs. If any is unknown or vague, ASK — do not assume:
--path; the subject)tf_module_analyzer vs tf_security_scanner)--min-severity; changes the report and CI pass/fail)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
# Analyze Terraform module structure and complexity
python scripts/tf_module_analyzer.py --path ./modules/vpc
# Scan for security misconfigurations
python scripts/tf_security_scanner.py --path ./environments/production
# JSON output for CI pipelines
python scripts/tf_security_scanner.py --path . --format json
# Recursive analysis of all modules
python scripts/tf_module_analyzer.py --path . --recursive
Analyzes Terraform modules for complexity, structure, dependencies, and documentation quality.
| Feature | Description |
|---|---|
| Complexity scoring | Scores modules by resource count, variable count, nesting |
| Dependency mapping | Maps module dependencies and data source usage |
| Variable analysis | Checks for missing types, defaults, descriptions |
| Output completeness | Validates output documentation and coverage |
| Naming conventions | Checks resource and variable naming patterns |
Scans Terraform configurations for security misconfigurations and compliance violations.
| Feature | Description |
|---|---|
| Open ports | Detects 0.0.0.0/0 CIDR in security groups |
| Public access | Flags public S3 buckets, databases, instances |
| Encryption gaps | Checks for missing encryption at rest and in transit |
| IAM overreach | Identifies wildcard actions and overly broad policies |
| Logging gaps | Verifies CloudTrail, flow logs, access logging |
# Security gate
python scripts/tf_security_scanner.py --path . --format json --min-severity high
if [ $? -ne 0 ]; then
echo "Security scan failed - blocking merge"
exit 1
fi
# Module quality check
python scripts/tf_module_analyzer.py --path . --recursive --format json
modules/vpc/
main.tf # Primary resources
variables.tf # Input variables with descriptions
outputs.tf # Module outputs
versions.tf # Required providers and versions
locals.tf # Local values and computed expressions
| Resource | Check | Rule |
|---|---|---|
| Security Groups | No 0.0.0.0/0 ingress | Restrict to known CIDRs |
| S3 Buckets | No public ACLs | Use bucket policies instead |
| RDS | No public access | Set publicly_accessible = false |
| EBS/S3/RDS | Encryption enabled | Add encryption configuration |
| IAM | No wildcard actions | Use least-privilege policies |
| CloudTrail | Enabled in all regions | is_multi_region_trail = true |
| VPC | Flow logs enabled | Create flow log resources |
| Score | Rating | Action |
|---|---|---|
| 0-30 | Low | No action needed |
| 31-60 | Medium | Consider splitting |
| 61-80 | High | Should refactor |
| 81-100 | Critical | Must refactor |
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This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.