dt-obs-aws
AWS cloud resources including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, databases, serverless, messaging, and cost optimization. Monitor AWS infrastructure, analyze resource usage, optimize costs, and ensure security compliance.
65
77%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/dt-obs-aws/SKILL.mdQuality
Discovery
82%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description is strong in specificity and trigger term coverage, listing numerous AWS services and concrete actions like monitoring, cost optimization, and security compliance. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know precisely when to select this skill. The AWS-specific terminology provides excellent distinctiveness.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about AWS infrastructure, cloud resources, EC2 instances, Lambda functions, or AWS cost optimization.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and services: EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, databases, serverless, messaging, cost optimization, monitoring, resource usage analysis, and security compliance. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific AWS services and actions (monitor, analyze, optimize, ensure compliance), but lacks an explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric. | 2 / 3 |
Trigger Term Quality | Includes many natural keywords users would say: 'AWS', 'EC2', 'RDS', 'Lambda', 'ECS', 'EKS', 'VPC', 'load balancers', 'serverless', 'cost optimization', 'security compliance'. These are terms users naturally use when asking about AWS infrastructure. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to AWS cloud resources with specific service names (EC2, RDS, Lambda, ECS/EKS, VPC). The AWS-specific terminology creates a distinct niche that is unlikely to conflict with non-AWS skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
72%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-structured AWS infrastructure skill with strong actionability through concrete DQL templates, specific entity types, and exact field paths. The progressive disclosure is excellent with clear routing to domain-specific reference files. The main weaknesses are some redundancy between the routing table and reference guide, inclusion of obvious best practices, and lack of validation/error-handling guidance in workflows.
Suggestions
Remove or consolidate the duplicate routing information — the 'When to Use This Skill' table and the 'Reference Guide' table overlap significantly.
Trim the Best Practices and Limitations sections to remove guidance Claude already knows (e.g., 'filter early', 'handle null values', 'limit results for exploration') and keep only Dynatrace-specific gotchas.
Add brief validation guidance: what to check when queries return empty results (e.g., verify AWS integration is configured, check entity type spelling, confirm account/region filters).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is generally efficient and avoids explaining basic AWS concepts Claude would know, but there's some redundancy — the reference guide table largely duplicates the 'When to Use This Skill' table, and the Best Practices/Limitations sections contain some obvious guidance (e.g., 'filter early', 'handle null values') that Claude already knows. | 2 / 3 |
Actionability | The skill provides fully executable DQL query templates with concrete syntax, specific entity type names, field paths for configuration parsing, and exact metric naming conventions. The traversal pairs and configuration field paths are highly specific and copy-paste ready. | 3 / 3 |
Workflow Clarity | The four core patterns are clearly sequenced and well-structured, and the routing table for which reference file to load is clear. However, there are no validation checkpoints or feedback loops — for example, no guidance on what to do when a query returns no results, how to verify entity types exist, or how to handle parsing failures from aws.object. | 2 / 3 |
Progressive Disclosure | Excellent progressive disclosure structure: the main file provides core patterns and concepts, with a well-organized reference table pointing to 13 specific reference files for deeper domain-specific queries. References are one level deep, clearly signaled with descriptive 'Key content' columns, and the routing table at the top makes navigation intuitive. | 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
- Dynatrace/dynatrace-for-ai
- Commit
4991356
- Reviewed
Table of Contents
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