capacity
Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.
92
92%
Does it follow best practices?
Impact
88%
1.35xAverage 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 hits all the marks. It provides specific concrete actions, comprehensive natural trigger terms, explicit use/don't-use guidance, and clear boundaries that distinguish it from related skills. The inclusion of a DO NOT USE FOR section with handoff guidance is particularly strong for avoiding skill conflicts.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: discovers available capacity, analyzes quota limits, compares availability, recommends optimal deployment locations. Also includes clear negative boundaries (what it does NOT do). | 3 / 3 |
Completeness | Clearly answers both 'what' (discovers capacity, analyzes quotas, compares availability, recommends deployment locations) and 'when' (explicit USE FOR and DO NOT USE FOR clauses with specific trigger scenarios). | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'find capacity', 'check quota', 'where can I deploy', 'best region for capacity', 'quota analysis', 'model availability', 'region comparison', 'check TPM availability'. These are highly natural phrases. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche (Azure OpenAI capacity discovery). The DO NOT USE FOR section explicitly delineates boundaries against related skills like deployment or quota increase requests, minimizing conflict risk. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%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-crafted skill with excellent workflow clarity and actionability — every phase has concrete commands, validation steps, and clear hand-off points. The progressive disclosure is strong with appropriate cross-references to related skills. Minor conciseness improvements could be made by trimming the 'When to Use' section and reducing duplication between PowerShell and bash examples where they're nearly identical.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but has some redundancy: the Quick Reference table and 'When to Use' section overlap with what should be in frontmatter/description. The dual PowerShell/bash examples throughout add bulk but are justified for cross-platform support. Phase 3.5 inline code could be more concise since the scripts should handle this. | 2 / 3 |
Actionability | Provides concrete, executable commands for every phase — specific script invocations with parameters, az CLI commands with exact query flags, and inline code for quota validation with jq/PowerShell. The example output table with specific values makes expected output crystal clear. | 3 / 3 |
Workflow Clarity | Excellent multi-phase workflow with clear sequencing (Phases 1-5), explicit validation checkpoints (Phase 3.5 quota validation), feedback loops (re-run Phase 2 if needed), and clear hand-off points. The annotated table example showing ✅/❌ states provides unambiguous decision criteria. | 3 / 3 |
Progressive Disclosure | Well-structured with a quick reference table up front, clear section hierarchy, and appropriate one-level-deep references to related skills (preset, customize, quota, parent router). Scripts are referenced by path without inlining their contents. Navigation between discovery and deployment skills is clearly signaled. | 3 / 3 |
Total | 11 / 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
915f809
- Reviewed
Table of Contents
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