CtrlK
BlogDocsLog inGet started
Tessl Logo

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

4.45x
Quality

85%

Does it follow best practices?

Impact

89%

4.45x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

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 workflow clarity and progressive disclosure — the 14-phase flow is clearly sequenced with validation checkpoints, and detailed implementation is appropriately deferred to reference files. However, the SKILL.md itself is somewhat verbose with redundant sections (comparison tables, checklist-style 'when to use' lists) and lacks directly executable code for the core workflow, relying entirely on the reference file for actionable implementation.

Suggestions

Trim the 'When to Use This Skill' section and comparison table — a single sentence distinguishing customize from preset would suffice, saving significant tokens.

Include at least one complete executable CLI command example for the core deployment step (Phase 13) directly in the SKILL.md rather than deferring all implementation to the reference file.

DimensionReasoningScore

Conciseness

The content includes useful tables and structured information but is verbose in places — the 'When to Use This Skill' section with checkmarks, the comparison table between customize vs preset, and the Quick Reference table all add bulk that Claude doesn't strictly need. The phase summaries table is reasonably efficient but the overall document is longer than necessary.

2 / 3

Actionability

The skill provides some concrete CLI commands (troubleshooting section, deployment commands) but the core workflow phases are described abstractly in a summary table, with actual executable scripts deferred entirely to a reference file. The SKILL.md itself doesn't contain the executable implementation — it says 'load references/customize-workflow.md for the full scripts and implementation details.'

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 flow includes feedback loops like 'if no capacity → cross-region fallback → user selects.'

3 / 3

Progressive Disclosure

The SKILL.md serves as a clear overview with well-signaled one-level-deep references to 'references/customize-workflow.md' for implementation details and 'references/customize-guides.md' for SKU guides and advanced topics. Content is appropriately split between overview (this file) and detailed implementation (reference files).

3 / 3

Total

10

/

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 an excellent skill description that covers all key dimensions thoroughly. It provides specific concrete actions, comprehensive trigger terms, explicit 'use when' and 'do not use when' guidance, and clear differentiation from related skills. The DO NOT USE FOR clause is a particularly strong addition for disambiguation in a multi-skill environment.

DimensionReasoningScore

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 concrete.

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 comprehensive trigger terms). The DO NOT USE FOR clause adds extra clarity for disambiguation.

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms users would say: '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 clear niche (custom/advanced Azure OpenAI deployment) and explicitly distinguishes 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

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

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.