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).
83
75%
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 an excellent skill description that clearly communicates specific capabilities (deploying Azure OpenAI models with intelligent region selection), provides comprehensive trigger terms via the USE FOR clause, and explicitly defines boundaries with the DO NOT USE FOR clause to prevent conflicts with related skills. The description is well-structured, uses third person voice appropriately, and balances detail with conciseness.
| 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 to optimal regions by analyzing capacity) 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 false matches. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche (Azure OpenAI model deployment with automatic region optimization). The DO NOT USE FOR clause explicitly delineates boundaries with a related 'customize' skill, minimizing conflict risk. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
50%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-organized overview of Azure OpenAI model deployment with clear workflow paths and useful error handling guidance. Its main weaknesses are the lack of complete executable command examples in the core workflow, missing validation/feedback loops for deployment operations, and some redundancy between sections. The progressive disclosure structure is reasonable but unverifiable without bundle files.
Suggestions
Add complete, copy-paste-ready command sequences for the core deployment workflow (both fast path and alternative region path) with actual parameter placeholders, rather than just listing command names in a table.
Add explicit validation checkpoints after deployment creation (e.g., 'Verify deployment succeeded: az cognitiveservices account deployment show ... --query provisioningState' with a retry/rollback step if it fails).
Remove the 'What This Skill Does' numbered list since it duplicates the Quick Workflow and Deployment Phases sections, or consolidate into a single workflow section.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is reasonably structured but includes some unnecessary verbosity—the 'What This Skill Does' section largely duplicates the workflow sections, and the deployment phases table repeats information from the quick workflow. The Notes section is lean, but overall there's room to tighten. | 2 / 3 |
Actionability | Key Azure CLI commands are listed in the phases table and error handling section, and the Advanced Usage section has executable commands. However, the core workflow lacks complete, copy-paste-ready command sequences—the phases table shows command fragments rather than full executable examples with proper parameters, and the Quick Workflow section is just a flowchart with no actual commands. | 2 / 3 |
Workflow Clarity | The two workflow paths (fast path and alternative region path) are clearly sequenced, and the phases table provides a logical progression. However, there are no explicit validation checkpoints or feedback loops—no step says 'verify deployment succeeded before proceeding' or 'if deployment fails, retry with X.' For a destructive/creation operation like deploying cloud resources, this gaps caps the score at 2. | 2 / 3 |
Progressive Disclosure | The skill references a workflow detail file at 'references/workflow.md' and links to a quota skill, which is good progressive disclosure structure. However, no bundle files were provided, so we can't verify these references exist. The main file also includes substantial inline detail (the full phases table, error handling table) that could arguably live in reference files, making the SKILL.md heavier than ideal for an overview. | 2 / 3 |
Total | 8 / 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
771a666
- Reviewed
Table of Contents
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