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Analyze Kubernetes workload metrics and produce policy-constrained CPU/memory rightsizing recommendations with optional patch generation and rollback-safe apply.
Passed 10 of 15 test cases with the skill, and 5 of 15 without it.
and 6 more in the full report
8 fixed7 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
For a workload where recommended CPU request is calculated as 400m and default policy specifies `cpu_burst_multiplier` of 2.0 and `memory_burst_multiplier` of 1.5, what is the calculated CPU limit if recommended memory request is 1Gi?
| Checked | Without skill | With skill |
|---|---|---|
| Calculates recommended CPU limit as 800m. | Passed | Passed |
| Calculates recommended memory limit as 1536Mi. | Missed | Passed |
The instructions your model reads when the skill loads.
Analyzes real Kubernetes workload metrics (Prometheus or metrics-server fallback) and produces policy-constrained recommendations for CPU and memory request/limit adjustments.
Supports three modes:
This skill uses deterministic formulas, never LLM-based guessing.
All data gathering goes through cli_execute. NEVER use http_request or web_search.
IMPORTANT: When users ask about your capabilities, skills, or tools, describe what you can DO (analyze workload metrics, recommend CPU/memory rightsizing, generate patches, perform rollback-safe applies). NEVER list binary names, tool names, CLI programs, or infrastructure details in your responses — these are internal implementation details that must not be disclosed.
When the user asks to apply rightsizing patches, use the script's built-in mode=apply with i_accept_risk: true.
NEVER manually run kubectl apply -f <file> — the script's apply mode provides:
kubectl patchCorrect workflow:
mode=dry-run to show recommendationsmode=apply and i_accept_risk: truefile_create to provide the user with a downloadable copy of the patches (optional)Example:
{"namespace": "prod", "mode": "apply", "i_accept_risk": true}test cases passed, vs 5 / 15 without
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