aws-solution-architect
Design AWS architectures for startups using serverless patterns and IaC templates. Use when asked to design serverless architecture, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, or migrate to AWS. Covers Lambda, API Gateway, DynamoDB, ECS, Aurora, and cost optimization.
84
85%
Does it follow best practices?
Impact
81%
1.24xAverage score across 6 eval scenarios
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a strong skill description that clearly communicates its purpose, scope, and trigger conditions. It uses third-person voice, lists concrete actions and specific AWS services, and includes an explicit 'Use when...' clause with natural trigger terms. The startup focus and enumeration of covered services further sharpen its distinctiveness.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: design AWS architectures, create CloudFormation templates, optimize AWS costs, set up CI/CD pipelines, migrate to AWS. Also names specific services: Lambda, API Gateway, DynamoDB, ECS, Aurora. | 3 / 3 |
Completeness | Clearly answers both 'what' (design AWS architectures using serverless patterns and IaC templates) and 'when' (explicit 'Use when...' clause listing five distinct trigger scenarios). The additional 'Covers' sentence reinforces scope. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'serverless architecture', 'CloudFormation templates', 'AWS costs', 'CI/CD pipelines', 'migrate to AWS', plus specific service names like Lambda, API Gateway, DynamoDB, ECS, Aurora. These are terms users naturally use when requesting these tasks. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: AWS serverless architecture for startups with specific service names and IaC focus. The combination of startup context, serverless patterns, and named AWS services makes it unlikely to conflict with generic coding or infrastructure skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
70%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-organized skill with strong workflow clarity and good progressive disclosure. Its main weaknesses are moderate verbosity (redundant sections like Quick Start, Input Requirements, and Output Formats that overlap with the workflow) and reliance on custom scripts that may not actually exist, reducing true actionability. The CloudFormation and CDK examples are valuable but the overall skill could be tightened significantly.
Suggestions
Remove or consolidate the Quick Start, Input Requirements, and Output Formats sections—they largely duplicate information already present in the workflow steps, adding ~80 lines of redundancy.
Clarify whether the Python scripts (architecture_designer.py, serverless_stack.py, cost_optimizer.py) are actual tools that ship with this skill or conceptual placeholders. If they don't exist, replace script invocations with direct actionable guidance Claude can follow without external tools.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is fairly well-structured but includes some unnecessary verbosity. The Quick Start section largely repeats information from the workflow steps, the Input Requirements table restates what's already in Step 1, and the Output Formats section adds little value. The tool descriptions also partially duplicate the workflow. Claude doesn't need explanations of what SaaS or MVP means. | 2 / 3 |
Actionability | The skill provides concrete CLI commands and example CloudFormation/CDK snippets, which is good. However, the core tools (architecture_designer.py, serverless_stack.py, cost_optimizer.py) are referenced as if they exist but are not provided or verifiable—Claude cannot actually execute these scripts. The CloudFormation and CDK examples are executable but partial. The Quick Start examples are descriptive rather than actionable (they describe expected results rather than providing executable steps). | 2 / 3 |
Workflow Clarity | The 6-step workflow is clearly sequenced with explicit validation checkpoints. Step 2 includes a validation checkpoint before proceeding. Step 6 provides detailed failure handling with specific commands for diagnosing failures, a fix-and-retry loop, and common failure causes with solutions. The deployment step covers multiple IaC tools. This is a well-structured workflow with appropriate feedback loops for destructive/deployment operations. | 3 / 3 |
Progressive Disclosure | The skill provides a clear overview with well-signaled one-level-deep references to architecture_patterns.md, service_selection.md, and best_practices.md. Content is appropriately split between the main skill (workflow, quick start, tools) and reference documents. The reference table at the bottom provides clear navigation. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- alirezarezvani/claude-skills
- Commit
f567c61
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.