APEX Skills is a collection of agent skills that provide AWS platform-engineering knowledge and workflows to coding agents. Engineers use it for tasks involving services such as Amazon EKS and Kubernetes. The catalogue entries are its skills and agents.
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 agentmods add agents/aws-samples/sample-apex-skills/workloads-recongit clone --depth 1 https://github.com/aws-samples/sample-apex-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/agents/aws-samples/sample-apex-skills/workloads-recon)<a href="https://agentmods.dev/agents/aws-samples/sample-apex-skills/workloads-recon"><img src="https://agentmods.dev/badge/agents/aws-samples/sample-apex-skills/workloads-recon.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00006 | $0.00566 |
| Opus 5 | $0.00003 | $0.00283 |
| Sonnet 5 | $0.00001 | $0.00113 |
| Haiku 4.5 | $0.00001 | $0.00057 |
Grade A, and why
workloads-recon 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.
The source is not reproduced here
Licensed MIT-0
The repository is licensed MIT-0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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 · 56 lines · 6 tokens per session scan A e8f3c3447797
workloads-recon is an agent published in the GitHub repository aws-samples/sample-apex-skills (56 stars, last pushed yesterday), licensed MIT-0. It adds 6 tokens to every session and 566 once invoked, about $0.0000 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 agents, from other repositories
infrastructure-architect
Infrastructure as Code specialist who designs Terraform modules, Kubernetes manifests, and cloud architecture. Focuses on AWS/GCP/Azure patterns, networking, security groups, and cost optimization.
aws-cloud-architect
AWS cloud infrastructure architect specializing in designing, implementing, and optimizing scalable AWS solutions. Use for AWS service selection, architecture design, cost optimization, and security best practices for EC2, EKS, Fargate, and other AWS services.
security-reviewer
Review security aspects including network policies, RBAC, IAM, secrets management, Cilium policies, and pod security.
terraform-security
Security analysis and hardening specialist for Terraform AWS Cognito configurations.
security-validator
Use during a deep security scan to adversarially validate ONE candidate finding. Attempts to refute it, assigns confidence 1-10; findings below 8 are dropped. The false-positive filter of the pipeline.
AGENTS
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