customize
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
88
85%
Does it follow best practices?
Impact
89%
4.45xAverage score across 3 eval scenarios
Passed
No known issues
Quality
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 covers all key dimensions thoroughly. It provides specific concrete actions, comprehensive trigger terms, explicit use/don't-use guidance, and clear differentiation from related skills. The DO NOT USE FOR clause is a particularly strong addition for reducing skill selection conflicts.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: step-by-step selection of model version, SKU types (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). Very detailed and actionable. | 3 / 3 |
Completeness | Clearly answers both 'what' (interactive guided deployment flow for Azure OpenAI models with full customization control) and 'when' (explicit USE FOR and DO NOT USE FOR clauses with detailed trigger scenarios). The DO NOT USE FOR clause adds extra clarity for disambiguation. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms including 'custom deployment', 'choose version', 'select SKU', 'set capacity', 'configure content filter', 'RAI policy', 'advanced deployment', 'PTU deployment', 'provisioned throughput'. These are terms users would naturally use when requesting this functionality. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche (custom/advanced Azure OpenAI deployment) and explicitly differentiates itself from a 'quick deployment to optimal region' skill via the DO NOT USE FOR clause, minimizing conflict risk. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
70%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 skill with excellent progressive disclosure and workflow clarity for a complex 14-phase deployment process. Its main weaknesses are moderate verbosity (the comparison table, checkmark lists, and quick reference table could be tightened) and the fact that actionable implementation details are entirely delegated to reference files, leaving the SKILL.md itself more descriptive than executable.
Suggestions
Trim the 'When to Use This Skill' section — the checkmark list and comparison table are verbose; a 2-line summary distinguishing customize vs preset would suffice.
Include at least one complete executable example in the SKILL.md itself (e.g., the final deployment CLI command with placeholder variables) so the skill is partially actionable without loading the reference file.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content includes useful tables and structure but has redundancy — the 'When to Use This Skill' section with checkmarks and the comparison table are somewhat verbose for Claude. The quick reference table and prerequisites section explain things Claude could infer. However, the phase summaries and error tables are reasonably efficient. | 2 / 3 |
Actionability | The skill provides some concrete CLI commands in troubleshooting and references executable commands like `az cognitiveservices account deployment create`, but the actual deployment workflow delegates all implementation details to a reference file. The SKILL.md itself contains no executable deployment code — only summaries of what each phase does, with a directive to load the reference file for the 'how'. | 2 / 3 |
Workflow Clarity | The 14-phase workflow is clearly sequenced with explicit validation checkpoints (Phase 7 validates capacity min/max/step, Phase 12 requires user review/approval before proceeding, capacity query failure blocks deployment). Cross-region fallback logic and error recovery paths are well-defined. The phase summary table clearly indicates what happens at each step. | 3 / 3 |
Progressive Disclosure | The skill provides a clear overview with well-signaled one-level-deep references: full implementation details in `references/customize-workflow.md`, SKU guides and advanced topics in `references/customize-guides.md`, and links to related skills. Content is appropriately split between overview (SKILL.md) and detailed implementation (reference files). | 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
- microsoft/github-copilot-for-azure
- Commit
a46a937
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.