CODEZ / Skill selection profile
aks-cost-optimizationScope, input evidence and acceptance checks
To investigate scheduling, scale-down or storage costs in an existing AKS cluster, first assess whether the evidence is sufficient before deciding to try this candidate.
Sources checked:
- Source repository
- microsoft/skills
- SKILL.md
.github/plugins/aks-skills/skills/aks-cost-optimization/SKILL.md- Repository stars
- 3,157
- Repository updated
- 2026-10-31
- Categories
- Cloud
- Last collected
License: License file needs review
CODEZ reviewed the main file and references at a fixed commit on 2026-10-29. This is editorial analysis: no Azure account was accessed, the Skill was not run, and no savings or client compatibility were measured.
Analysis this candidate can support
This Skill targets advanced cost-efficiency analysis of existing clusters. Overall AKS cost assessment has a separate entry point; checking only node placement or disks does not complete that assessment.
How evidence changes a conclusion
| Scenario | Check first | Still to validate |
|---|---|---|
| Node placement and capacity | Check allocatable CPU, memory and Pod slots, accounting for every scheduled Pod, DaemonSet and overhead. Assess availability zones and placement constraints separately. | A theoretical node lower bound estimated from requests is not a validated, achievable scale-down count. Without evidence on affinity, isolation or availability, the scenario remains unconfirmed. |
| Disk ownership and costs | Retain an exact PVC → PV → Azure resource mapping and correlate actual billed costs at the same scope using exact resource IDs. Record historical metric intervals, units and gaps. | Having no PV does not establish that a disk can be deleted. Check ownership, attachments, backup/restore references and owner requirements. Without billing or representative metrics, cost or utilization is unknown, not 0. |
Acceptance checks before delivery
CODEZ recommends tying each conclusion to the target resource, evidence interval, constraints, cost basis and unresolved points. Record theoretical models, proposals awaiting validation and executed changes separately. This is an unexecuted acceptance design; actual configuration changes still require separate confirmation.
How to choose an Agent Skill: from stars to a practical trial ↗
The purpose and workflow passages below are upstream material, organized and translated for reading. They are distinct from the separately labeled Codez editorial analysis.
What this Skill does
Analyze advanced AKS cost efficiency. WHEN: "AKS NAP readiness", "AKS bin packing", "AKS node scaling bottleneck", "AKS blocked scale-down", "AKS storage cost". DO NOT USE AS DIRECT ENTRY FOR: overall AKS cost assessments or rightsizing/VPA/CAS/Spot (azure-kubernetes); spend/anomalies/commitments (cost-analysis/cost-optimization); incidents (aks-troubleshooting).
How the upstream workflow works
Workflow/Steps
Bind the subscription, cluster, resource group, and kube context. Route to NAP readiness, bin-packing, node-scaling bottlenecks, or storage optimization. When invoked for AKS commitment context, use the commitment-demand handoff and return demand evidence without benefit analysis or a transaction. Keep reads non-mutating; require approval for every change.
Upstream passage · L24 ↗When to Use This Skill
Use for advanced existing-cluster analysis requiring scheduling, placement, or verified storage mapping. Route overall AKS cost assessments to azure-kubernetes, spend/anomalies to cost-analysis, commitments to cost-optimization, and incidents to aks-troubleshooting when those skills are available. When called from an overall assessment, return findings for its ranked report.
MCP Tools
Prefer fitting Azure MCP reads. Never invent tools or use az/kubectl without approved shell access and a target-bound context.
Requirements and setup
No short requirements passage was selected from this file. This does not mean the Skill has no dependencies. Check the repository setup instructions and referenced files.
Limits and quality checks
No separate limits passage was selected from this file. This does not mean the Skill is safe for every input or environment. Review the complete source and validate your own result.
Start with a safe trial
- Check the supported host and the repository installation instructions. Keep the Skill directory and its referenced scripts, assets and documentation together; SKILL.md alone may omit dependencies.
- Give the agent your real input, desired output and acceptance criteria. Invocation syntax and available tools depend on the host; this site does not assume a universal install command.
- Try the source workflow in a disposable project or on a copy. Review operations that change files, remote services or billable resources before allowing them.
- Validate the output against the source quality checks and your own requirements. A successful trigger or a high repository Star count does not establish a correct result.
Read further in the source
Related Skills
Translation and scope
This reading guide selects passages from the pinned upstream SKILL.md. Translation is assisted. It is not a complete manual or a claim of tested compatibility. Read the original and its referenced files before use.
This introduction refers to the pinned version below; current repository activity and collection time are shown separately.
- Pinned source
- Read the original ↗
- Source retrieved
- Source commit
00d66a64919edca5bca2c673373444e36a4b5461- Source SHA-256
ea9fe2e1883532a1e8d9a8a33d174a00498363733b0ea74fdc8f8eae1303f4c7