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cost-optimization

Optimize existing Azure resources and analyze Reservations or Savings Plans. WHEN: "optimize Azure costs", "reduce cloud spending", "rightsize resources", "find idle resources", "orphaned disk", "deleted VM still charged", "public IP still charging", "reservation utilization", "Savings Plan coverage", "commitment recommendation", "why is pay-as-you-go still charged". DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or governance.

72

Quality

90%

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SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tight, well-structured overview that maximizes token efficiency and routes to real, well-organized reference files with conditional second-level loading. The main improvement opportunities are making query validation an explicit workflow checkpoint and surfacing the remaining reference files in the top-level index.

Suggestions

Promote query validation into an explicit numbered workflow step (e.g. between steps 2 and 3: 'Validate each Resource Graph query with validate_query before executing') so the checkpoint is not implicit.

Add a row or link in the Quick Reference for references/resource-graph.md and references/report-template.md so all reference files are discoverable from the SKILL.md index rather than only via optimization.md.

Include one concrete example tool invocation (e.g. a `query_costs` call shape with grouping by ServiceName and PricingModel) in the body to make the core guidance copy-paste ready.

DimensionReasoningScore

Conciseness

The 34-line body is lean with zero concept explanations or padding: every section (Quick Reference table, Workflow, Error Handling table) carries operational content, e.g. "Never transform MCP results in a shell or interpreter; request validated server-side projection". It assumes Claude's competence throughout.

5 / 5

Actionability

As an instruction-only skill it gives concrete, executable direction (named tools like `list_benefit_utilization`, specific error actions like "Retry once; then report the trace ID") and properly delegates detail to real referenced workflows. Not 5: the body itself contains no example tool call or query shape, leaving a minor gap before copy-paste-ready guidance.

4 / 5

Workflow Clarity

A clear 5-step sequence is paired with an Error Handling table that provides recovery actions per failure mode (per-currency grouping, "State the gap; do not invent values", retry-then-trace-ID), and safety is explicit ("Recommend changes only; do not delete, resize, purchase, or deploy"). Not 5: "Validate queries" in the MCP Tools section is a mention rather than an explicit validation checkpoint inside the numbered workflow. The destructive/batch cap does not apply since destructive actions are explicitly prohibited.

4 / 5

Progressive Disclosure

Scored against the actual bundle: the Quick Reference table routes intents to two real workflow files (references/optimization.md, references/commitments.md), and the tool-fallback link resolves; second-level files (references/services/*.md, resource-graph.md, report-template.md) are conditionally loaded and clearly signaled from within optimization.md rather than buried. Not 5: resource-graph.md and report-template.md are not surfaced in the SKILL.md index itself, only reachable through a referenced file.

4 / 5

Total

17

/

20

Passed

Description

95%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong frontmatter description: explicit what/when/exclude structure, comprehensive natural trigger phrases including user-symptom utterances, and low conflict risk thanks to the exclusion list. The only minor gap is that the what-clause is slightly broader than the enumerated trigger coverage.

DimensionReasoningScore

Specificity

"Optimize existing Azure resources and analyze Reservations or Savings Plans" names the domain plus two concrete capability clusters, and "DO NOT USE FOR: cost spikes, forecasts, pricing estimates, budgets, or governance" sharpens scope. It falls just short of anchor 5 because the what-clause does not enumerate what optimization covers (rightsizing, idle-resource detection live only in the trigger list).

4 / 5

Completeness

It explicitly answers what ("Optimize existing Azure resources and analyze Reservations or Savings Plans") and when ("WHEN: 'optimize Azure costs', ..."), mirroring the anchor-5 example structure, and adds explicit exclusions. Not 4: the when-clause is fully explicit with concrete trigger phrases, not merely adequate.

5 / 5

Trigger Term Quality

The WHEN clause lists comprehensive natural phrasings users would actually say, including symptom-style utterances ("deleted VM still charged", "public IP still charging", "why is pay-as-you-go still charged") and synonyms ("rightsize", "find idle resources", "Savings Plan coverage"). Coverage is comprehensive with no obvious missing variations.

5 / 5

Distinctiveness Conflict Risk

Clear niche (Azure waste/rightsizing/commitments) with distinct, service-specific triggers, and the "DO NOT USE FOR" list actively prevents mis-triggering against adjacent cost-management skills (budgets, forecasts, pricing). Voice is third person, so no voice penalty applies.

5 / 5

Total

19

/

20

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
microsoft/GitHub-Copilot-for-Azure
Reviewed

Table of Contents

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