Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aj-geddes/useful-ai-prompts --skill autoscaling-configurationgit clone --depth 1 https://github.com/aj-geddes/useful-ai-promptsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration)<a href="https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration"><img src="https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration"><img src="https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/autoscaling-configuration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.00556 |
| Opus 5 | $0.00014 | $0.00278 |
| Sonnet 5 | $0.00006 | $0.00111 |
| Haiku 4.5 | $0.00003 | $0.00056 |
Grade A, and why
autoscaling-configuration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autoscaling Configuration
Table of Contents
Overview
Implement autoscaling strategies to automatically adjust resource capacity based on demand, ensuring cost efficiency while maintaining performance and availability.
When to Use
- Traffic-driven workload scaling
- Time-based scheduled scaling
- Resource utilization optimization
- Cost reduction
- High-traffic event handling
- Batch processing optimization
- Database connection pooling
Quick Start
Minimal working example:
# hpa-configuration.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: myapp-hpa
namespace: production
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: myapp
minReplicas: 2
maxReplicas: 20
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 70
- type: Resource
resource:
name: memory
target:
type: Utilization
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Kubernetes Horizontal Pod Autoscaler | Kubernetes Horizontal Pod Autoscaler |
| AWS Auto Scaling | AWS Auto Scaling |
| Custom Metrics Autoscaling | Custom Metrics Autoscaling |
| Autoscaling Script | Autoscaling Script |
| Monitoring Autoscaling | Monitoring Autoscaling |
Best Practices
✅ DO
- Set appropriate min/max replicas
- Monitor metric aggregation window
- Implement cooldown periods
- Use multiple metrics
- Test scaling behavior
- Monitor scaling events
- Plan for peak loads
- Implement fallback strategies
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/autoscaling-script.md 1.3 KB
- references/aws-auto-scaling.md 3.1 KB
- references/custom-metrics-autoscaling.md 1.2 KB
- references/kubernetes-horizontal-pod-autoscaler.md 1.8 KB
- references/monitoring-autoscaling.md 1.4 KB
- scripts/validate-config.sh 427 B runs code
- templates/config-starter.yaml 453 B
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 100 lines · 28 tokens per session scan A 52a2efc54714
autoscaling-configuration is a skill published in the GitHub repository aj-geddes/useful-ai-prompts (338 stars, last pushed 6mo ago), licensed MIT. It adds 28 tokens to every session and 556 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
gke-compute-classes
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
azure-mgmt-botservice-dotnet
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
cloud-architect
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost…