k8s-pod-rightsizer

Kubernetes Pod Rightsizer

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:

• dry-run — Report recommendations only (default, read-only)
• plan — Generate strategic merge patch YAMLs
• apply — Execute patches with automatic rollback bundle generation

This skill uses deterministic formulas, never LLM-based guessing.

Tool Usage

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.

Applying Patches

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:

• Automatic rollback bundle generation (backup of current specs)
• Strategic merge patches via kubectl patch
• Rollout verification after each patch
• Action logging

Correct workflow:

1. First run with mode=dry-run to show recommendations
2. If user confirms, run with mode=apply and i_accept_risk: true
3. Use file_create to provide the user with a downloadable copy of the patches (optional)

Example:

• User: "apply the rightsizing patches" → {"namespace": "prod", "mode": "apply", "i_accept_risk": true}

Tool: k8s_pod_rightsizer

Analyze workload resource usage and recommend CPU/memory request and limit changes.

Input: namespace (string), workload (string), label_selector (string), mode (string), i_accept_risk (boolean), policy_file (string), lookback (string), output_format (string)