preset
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
85
78%
Does it follow best practices?
Impact
96%
4.17xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugin/skills/microsoft-foundry/models/deploy-model/preset/SKILL.mdQuality
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 excels across all dimensions. It provides specific capabilities, comprehensive trigger terms, explicit use/don't-use guidance, and clear boundaries against related skills. The DO NOT USE FOR clause is particularly effective at reducing conflict risk with the companion 'customize' skill.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: deploys Azure OpenAI models, analyzes capacity across regions, checks current region first, shows alternatives. These are clear, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (deploys Azure OpenAI models by analyzing capacity across regions) and 'when' (explicit USE FOR and DO NOT USE FOR clauses with specific trigger scenarios and boundary conditions). | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would say: 'quick deployment', 'optimal region', 'best region', 'automatic region selection', 'fast setup', 'multi-region capacity check', 'high availability deployment', 'deploy to best location'. Also includes negative triggers to reduce conflicts. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with explicit DO NOT USE FOR clauses that delineate boundaries against a 'customize' skill. The focus on automatic/optimal region selection creates a clear niche distinct from manual configuration skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
57%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a well-structured overview of Azure OpenAI model deployment with good organization, clear workflow paths, and useful error handling tables. Its main weaknesses are moderate redundancy between sections and insufficient executable detail in the core workflow—key commands are referenced but not fully fleshed out with complete, copy-paste-ready syntax. Adding explicit validation checkpoints in the workflow would strengthen reliability for this multi-step deployment process.
Suggestions
Add explicit validation checkpoints in the workflow (e.g., 'Verify deployment status before proceeding' with the exact az CLI command), especially after the deploy step—this is a multi-step cloud operation where validation is critical.
Provide complete, executable command examples for the core deployment flow rather than abbreviated commands with ellipsis—include full parameter syntax with placeholder variables that can be substituted.
Remove the 'What This Skill Does' numbered list since it duplicates the Quick Workflow and Deployment Phases sections, reducing redundancy.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably structured but includes some redundancy—the 'What This Skill Does' numbered list largely duplicates the Quick Workflow and Deployment Phases sections. The Notes section and some table entries could be tightened. However, it avoids explaining basic concepts Claude already knows. | 2 / 3 |
Actionability | The skill provides specific Azure CLI commands in the deployment phases table and error handling section, plus some executable bash examples in Advanced Usage. However, the core workflow lacks fully executable, copy-paste-ready command sequences—many commands use ellipsis or placeholders without complete syntax, and the main deployment flow defers to a reference file for detailed steps. | 2 / 3 |
Workflow Clarity | The two workflow paths (fast path and alternative region path) are clearly diagrammed, and the phased table provides good sequencing. However, there are no explicit validation checkpoints or feedback loops (e.g., verify deployment succeeded before proceeding, retry logic on failure). For a multi-step deployment operation, the absence of validate-then-proceed gates is a notable gap. | 2 / 3 |
Progressive Disclosure | The skill provides a clear overview with well-organized sections (quick workflow, phases table, error handling, advanced usage) and appropriately references a detailed workflow file and related skills with one-level-deep links. Content is well-split between overview and detail. | 3 / 3 |
Total | 9 / 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
- microsoft/github-copilot-for-azure
- Commit
a3bdc6e
- Reviewed
Table of Contents
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