azure-compute
Recommend Azure VM sizes, VM Scale Sets (VMSS), and configurations based on workload requirements, performance needs, and budget constraints. No Azure account required — uses public documentation and the Azure Retail Prices API. WHEN: recommend VM size, which VM should I use, choose Azure VM, VM for web/database/ML/batch/HPC, GPU VM, compare VM sizes, cheapest VM, best VM for workload, VM pricing, cost estimate, burstable/compute/memory/storage optimized VM, confidential computing, VM trade-offs, VM families, VMSS, scale set recommendation, autoscale VMs, load balanced VMs, VMSS vs VM, scale out, horizontal scaling, flexible orchestration.
Install with Tessl CLI
npx tessl i github:microsoft/azure-skills --skill azure-compute93
Quality
92%
Does it follow best practices?
Impact
89%
1.32xAverage score across 3 eval scenarios
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 an excellent skill description that hits all the marks. It clearly specifies what the skill does (Azure VM recommendations), provides helpful context (no Azure account required, uses public APIs), and includes a comprehensive explicit 'WHEN:' clause with extensive natural trigger terms covering various user scenarios from cost optimization to workload-specific recommendations.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Recommend Azure VM sizes, VM Scale Sets (VMSS), and configurations based on workload requirements, performance needs, and budget constraints.' Also specifies data sources used (public documentation and Azure Retail Prices API). | 3 / 3 |
Completeness | Clearly answers both 'what' (recommend Azure VM sizes, VMSS, and configurations based on requirements) and 'when' with an explicit 'WHEN:' clause containing comprehensive trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say, including variations like 'recommend VM size', 'which VM should I use', 'cheapest VM', 'best VM for workload', 'GPU VM', 'VM for web/database/ML/batch/HPC', and specific technical terms like 'burstable', 'VMSS', 'autoscale'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear Azure VM-specific niche. The combination of 'Azure VM', 'VMSS', 'VM families', and Azure-specific terminology makes it unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%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-crafted skill with excellent actionability and workflow clarity. It provides concrete guidance with specific URLs, decision trees, and validation checkpoints. The main weakness is moderate verbosity—some content is duplicated between the decision tree and summary table, and a few explanatory phrases could be trimmed without losing clarity.
Suggestions
Consolidate the VM vs VMSS decision tree and the summary table in Step 2—they convey overlapping information and one could be removed or significantly shortened.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some redundancy (e.g., the decision tree and table in Step 2 overlap significantly, and some guidance like 'Ask the user for (infer when possible)' could be trimmed). The tables are helpful but some explanatory text could be tightened. | 2 / 3 |
Actionability | Provides concrete, executable guidance throughout: specific API endpoints to fetch, exact URL patterns for documentation, clear decision trees, and specific SKU names. The workflow steps are copy-paste ready with actual commands and URLs. | 3 / 3 |
Workflow Clarity | Excellent multi-step workflow with clear sequencing (Steps 1-6), explicit validation checkpoints (REQUIRED fetch steps with fallback warnings), and error handling table. The decision tree for VM vs VMSS provides clear branching logic with feedback loops for failed web_fetch calls. | 3 / 3 |
Progressive Disclosure | Well-structured with clear overview in main file and one-level-deep references to specialized guides (vm-families.md, retail-prices-api.md, vmss-guide.md). Navigation is clear with inline links and a dedicated References section at the end. | 3 / 3 |
Total | 11 / 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.
- Reviewed
Table of Contents
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