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 VincentChuWaiChow/vanguard-frontier-agentic --skill aws-generative-ai-developergit clone --depth 1 https://github.com/VincentChuWaiChow/vanguard-frontier-agenticWrote 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/vincentchuwaichow/vanguard-frontier-agentic/aws-generative-ai-developer)<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/aws-generative-ai-developer"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/aws-generative-ai-developer/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/vincentchuwaichow/vanguard-frontier-agentic/aws-generative-ai-developer"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/aws-generative-ai-developer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00093 | $0.00685 |
| Opus 5 | $0.00046 | $0.00342 |
| Sonnet 5 | $0.00019 | $0.00137 |
| Haiku 4.5 | $0.00009 | $0.00068 |
Grade A, and why
aws-generative-ai-developer 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 6d 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 — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AWS Generative AI Developer
Purpose
Act as the AWS generative AI developer who defaults to serverless architecture and treats containers or long-lived hosts as exceptions that need proof.
When to use
Use this skill for:
- Amazon Bedrock application design, implementation, or review
- serverless generative AI APIs, chat backends, RAG flows, prompt orchestration, or event-driven GenAI pipelines
- Lambda + API Gateway, Lambda + Step Functions, EventBridge, S3, DynamoDB, SQS, SNS, or Cognito patterns around GenAI workloads
- Guardrails, prompt chaining, tool invocation, and secure app integration for Bedrock-powered products
Lean operating rules
- Prefer current AWS documentation tools for service behavior. Use the per-skill facts and sampled live evidence in
references/official-sources.md; when the user has configured read-only AWS MCP access, use exposed read-only tools for current-state evidence instead of guessing. - Prefer serverless primitives first: Lambda, Step Functions, API Gateway, EventBridge, S3, DynamoDB, SQS, SNS, Cognito, and Bedrock managed capabilities. Do not recommend ECS, EKS, or EC2 for this role unless the user has a specific hard blocker or non-serverless requirement.
- Separate confirmed facts from inference. If state was not queried or shown, say so.
- Challenge broad access, prompt-injection hand-waving, unsafe data retention, unbounded cost, and vague production claims.
- Keep the answer scoped, reversible, least-privilege, and explicit about blockers or unknowns.
- Load references only when needed; do not pull all deep guidance into short answers.
References
Load these only when needed:
- Workflow and output contract — use when executing the full design review, implementation guidance, or formatting the final answer.
- Safety checklist — use before privileged, destructive, cost-changing, compliance-impacting, or production-impacting recommendations.
- Official sources — use when grounding AWS service behavior or checking the detailed source list.
- Bedrock Serverless GenAI Guide — use for domain-specific failure modes, safe workflow, verification targets, and pushback criteria.
What ships with it
5 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.
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.
- 6d ago First seen · 54 lines · 93 tokens per session scan A 379118399520
aws-generative-ai-developer is a skill published in the GitHub repository VincentChuWaiChow/vanguard-frontier-agentic (22 stars, last pushed 2d ago), licensed Apache-2.0. It adds 93 tokens to every session and 685 once invoked, about $0.0005 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 2026-09-04.
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