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 FOR' and 'DO NOT USE FOR' clauses, and clear boundaries that distinguish it from related skills. The inclusion of negative triggers (DO NOT USE FOR) is a particularly strong feature that reduces conflict risk with adjacent skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: discovers available capacity, analyzes quota limits, compares availability, recommends optimal deployment locations. Also specifies scope (across regions and projects) and constraint (based on capacity requirements). | 3 / 3 |
Completeness | Clearly answers both 'what' (discovers capacity, analyzes quotas, compares availability, recommends deployment locations) and 'when' (explicit USE FOR clause with trigger terms). Additionally includes a DO NOT USE FOR section that further clarifies boundaries and prevents misuse. | 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', 'check TPM availability', 'model availability', 'region comparison'. These are highly natural phrases a user would actually type. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: Azure OpenAI capacity discovery specifically. The DO NOT USE FOR section explicitly delineates boundaries against related skills (deployment, quota increases, listing deployments), significantly reducing 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 strong actionability and workflow clarity. The multi-phase discovery process is clearly sequenced with validation checkpoints, error handling, and explicit hand-off points. Minor conciseness improvements could be made by trimming the 'When to Use' section and tightening the Quick Reference table, but overall the content is effective and well-organized.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but has some redundancy — the Quick Reference table and 'When to Use' section overlap with what the YAML frontmatter description already covers. The dual PowerShell/bash examples throughout add bulk but are justified for cross-platform support. Phase 3.5 inline code could be more concise. | 2 / 3 |
Actionability | Provides concrete, executable commands for every phase — specific script invocations with parameters, az CLI commands with exact query syntax, and jq expressions for parsing. The quota validation code in Phase 3.5 is detailed and copy-paste ready. | 3 / 3 |
Workflow Clarity | Excellent multi-phase workflow with clear sequencing, explicit validation steps (Phase 3.5 quota validation after capacity discovery), error handling table with resolutions, and a clear decision tree in Phase 4 for next actions. The feedback loop of 'if no quota → hand off to quota skill' is well-defined. | 3 / 3 |
Progressive Disclosure | Well-structured with clear sections progressing from quick reference to detailed workflow. References to related skills (preset, customize, quota, parent router) are one level deep and clearly signaled with relative paths. The scripts table provides a clean overview without inlining script contents. | 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/azure-skills
- Commit
02a614f
- Reviewed
Table of Contents
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