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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

4.17x
Quality

75%

Does it follow best practices?

Impact

96%

4.17x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./plugin/skills/microsoft-foundry/models/deploy-model/preset/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

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 solid structural overview of Azure OpenAI model deployment with clear workflow paths and useful error handling guidance. Its main weaknesses are the lack of fully executable command examples in the core workflow, missing validation checkpoints for a multi-step deployment process, and some redundancy between sections. The referenced bundle file (references/workflow.md) is not provided, making it impossible to verify the progressive disclosure chain.

Suggestions

Add explicit validation checkpoints in the workflow (e.g., 'Verify deployment status before proceeding' after step 7, with the exact az command to check provisioning state)

Replace the phases table command fragments with complete, templated command examples that are copy-paste ready (e.g., full `az rest` URL with placeholders for subscription, resource group, etc.)

Remove the 'What This Skill Does' numbered list since it duplicates the Quick Workflow and Deployment Phases sections

Provide the referenced references/workflow.md bundle file, or inline the critical deployment steps if the reference doesn't exist

DimensionReasoningScore

Conciseness

The content is reasonably structured but includes some unnecessary verbosity, such as the 'What This Skill Does' section which largely duplicates the workflow sections, and the Notes section with minimal content. The deployment phases table is useful but could be tighter.

2 / 3

Actionability

The skill provides real Azure CLI commands in the phases table and error handling section, plus some executable bash examples in Advanced Usage. However, the core workflow lacks complete, copy-paste-ready command sequences — the phases table lists command fragments rather than fully executable examples with parameters filled in or clearly templated.

2 / 3

Workflow Clarity

The two workflow paths (fast path and alternative region path) are clearly sequenced, and the phases table provides good structure. However, there are no explicit validation checkpoints or feedback loops — for a deployment operation that could fail at multiple stages, there's no 'verify before proceeding' step or error recovery loop built into the workflow itself.

2 / 3

Progressive Disclosure

The skill references a workflow detail file (references/workflow.md) and related skills, which is good progressive disclosure structure. However, no bundle files were provided, so the referenced workflow.md cannot be verified to exist. The main file includes substantial detail (phases table, error handling table) that could arguably live in reference files, making the SKILL.md longer than ideal for an overview.

2 / 3

Total

8

/

12

Passed

Description

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 concrete actions, comprehensive trigger terms, explicit use/don't-use guidance, and clear boundaries with related skills. The DO NOT USE FOR clause is particularly effective at reducing conflict risk with the companion 'customize' skill.

DimensionReasoningScore

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 with other skills).

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'. Good coverage of variations.

3 / 3

Distinctiveness Conflict Risk

Excellent distinctiveness with explicit DO NOT USE FOR clauses that delineate boundaries with a 'customize' skill. The focus on automatic/optimal region selection creates a clear niche distinct from custom configuration tasks.

3 / 3

Total

12

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
microsoft/github-copilot-for-azure
Reviewed

Table of Contents

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