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 clearly defines its scope, provides comprehensive trigger terms, and explicitly delineates boundaries with related skills. The inclusion of both USE FOR and DO NOT USE FOR clauses makes it highly effective for skill selection. The description uses proper third-person voice throughout and is specific to a well-defined domain.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: discovers available capacity across regions and projects, analyzes quota limits, compares availability, and recommends optimal deployment locations 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). Also includes helpful DO NOT USE FOR boundaries. | 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', 'multi-project capacity search', 'quota analysis', 'model availability', 'region comparison', 'check TPM availability'. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche (Azure OpenAI capacity discovery). The DO NOT USE FOR clause 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-structured, highly actionable skill with excellent workflow clarity and progressive disclosure. The multi-phase workflow with explicit validation checkpoints (especially Phase 3.5 quota validation) demonstrates best practices for complex operations. The main weakness is moderate verbosity — the Quick Reference table, 'When to Use' section, and some inline explanations could be trimmed without losing clarity.
Suggestions
Remove or significantly trim the Quick Reference table and 'When to Use This Skill' section — these largely duplicate the frontmatter description and add tokens without new information for Claude.
Tighten Phase 3.5 by removing the explanatory prose ('Model capacity shows what the platform can support, but subscription quota limits what this specific user can deploy') and letting the code speak for itself.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Generally efficient but includes some unnecessary elements like the 'When to Use This Skill' section (which duplicates frontmatter intent), the Quick Reference table restating obvious things, and some verbose inline explanations. The Phase 3.5 quota validation section is quite lengthy with code that could be tighter. | 2 / 3 |
Actionability | Provides concrete, executable commands for every phase — specific script invocations with parameters, az CLI commands, PowerShell and bash variants, and jq queries for parsing. The quota validation code is copy-paste ready with clear variable substitution patterns. | 3 / 3 |
Workflow Clarity | Excellent multi-phase workflow with clear sequencing (Phases 1-5), explicit validation checkpoints (Phase 3.5 quota validation with annotated results), feedback loops (re-run Phase 2 option), and clear decision points with numbered options at Phase 4. Error handling table provides resolution paths. | 3 / 3 |
Progressive Disclosure | Well-structured with clear one-level-deep references to related skills (preset, customize, quota, parent router). Scripts are referenced by path without inlining their contents. The skill stays focused on discovery while cleanly handing off to other skills for deployment and quota management. | 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
9d594ab
- Reviewed
Table of Contents
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