AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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 sickn33/agentic-awesome-skills --skill aws-cost-optimizergit clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsWrote 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/sickn33/agentic-awesome-skills/aws-cost-optimizer)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/aws-cost-optimizer"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/aws-cost-optimizer/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/sickn33/agentic-awesome-skills/aws-cost-optimizer"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/aws-cost-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector 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 | $0.00019 | $0.01557 |
| Opus 5 | $0.00010 | $0.00779 |
| Sonnet 5 | $0.00004 | $0.00311 |
| Haiku 4.5 | $0.00002 | $0.00156 |
Grade A, and why
aws-cost-optimizer 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 5d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- aws-cost-optimizer — 100% identical, 0 lines differ
- aws-cost-optimizer — 100% identical, 0 lines differ
- aws-cost-optimizer — 100% identical, 0 lines differ
- aws-cost-optimizer — 100% identical, 0 lines differ
- aws-cost-optimizer — 100% identical, 0 lines differ
- aws-cost-optimizer — 100% identical, 0 lines differ
- aws-cost-optimizer — 92% identical, 5 lines differ
- aws-cost-optimizer — 92% identical, 5 lines differ
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AWS Cost Optimizer
Analyze AWS spending patterns, identify waste, and provide actionable cost reduction strategies.
When to Use This Skill
Use this skill when you need to analyze AWS spending, identify cost optimization opportunities, or reduce cloud waste.
Core Capabilities
Cost Analysis
- Parse AWS Cost Explorer data for trends and anomalies
- Break down costs by service, region, and resource tags
- Identify month-over-month spending increases
Resource Optimization
- Detect idle EC2 instances (low CPU utilization)
- Find unattached EBS volumes and old snapshots
- Identify unused Elastic IPs
- Locate underutilized RDS instances
- Find old S3 objects eligible for lifecycle policies
Savings Recommendations
- Suggest Reserved Instance/Savings Plans opportunities
- Recommend instance rightsizing based on CloudWatch metrics
- Identify resources in expensive regions
- Calculate potential savings with specific actions
AWS CLI Commands
Get Cost and Usage
# Last 30 days cost by service
aws ce get-cost-and-usage \
--time-period Start=$(date -d '30 days ago' +%Y-%m-%d),End=$(date +%Y-%m-%d) \
--granularity MONTHLY \
--metrics BlendedCost \
--group-by Type=DIMENSION,Key=SERVICE
# Daily costs for current month
aws ce get-cost-and-usage \
--time-period Start=$(date +%Y-%m-01),End=$(date +%Y-%m-%d) \
--granularity DAILY \
--metrics UnblendedCost
Find Unused Resources
# Unattached EBS volumes
aws ec2 describe-volumes \
--filters Name=status,Values=available \
--query 'Volumes[*].[VolumeId,Size,VolumeType,CreateTime]' \
--output table
# Unused Elastic IPs
aws ec2 describe-addresses \
--query 'Addresses[?AssociationId==null].[PublicIp,AllocationId]' \
--output table
# Idle EC2 instances (requires CloudWatch)
aws cloudwatch get-metric-statistics \
--namespace AWS/EC2 \
--metric-name CPUUtilization \
--dimensions Name=InstanceId,Value=i-xxxxx \
--start-time $(date -u -d '7 days ago' +%Y-%m-%dT%H:%M:%S) \
--end-time $(date -u +%Y-%m-%dT%H:%M:%S) \
--period 86400 \
--statistics Average
# Old EBS snapshots (>90 days)
aws ec2 describe-snapshots \
--owner-ids self \
--query 'Snapshots[?StartTime<=`'$(date -d '90 days ago' --iso-8601)'`].[SnapshotId,StartTime,VolumeSize]' \
--output table
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.
- 5d ago First seen · 199 lines · 19 tokens per session scan A 43cdf380dfef
aws-cost-optimizer is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,230 stars, last pushed yesterday), licensed MIT. It adds 19 tokens to every session and 1,557 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 2026-09-05.
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