Sample Agent Skills for Builders is a collection of reusable skills that extend AI coding agents with AWS, CDK, security, testing, and engineering workflows. Developers can install the skills for practical AWS development tasks or use the repository as a model for creating their own agent skills. The catalogue entries are skills and instructions from this collection.
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 aws-samples/sample-agent-skills-for-builders --skill agentic-responsible-ai-assessmentgit clone --depth 1 https://github.com/aws-samples/sample-agent-skills-for-buildersWrote 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/aws-samples/sample-agent-skills-for-builders/agentic-responsible-ai-assessment)<a href="https://agentmods.dev/skills/aws-samples/sample-agent-skills-for-builders/agentic-responsible-ai-assessment"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agent-skills-for-builders/agentic-responsible-ai-assessment/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/aws-samples/sample-agent-skills-for-builders/agentic-responsible-ai-assessment"><img src="https://agentmods.dev/badge/skills/aws-samples/sample-agent-skills-for-builders/agentic-responsible-ai-assessment.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 | $0.00118 | $0.04315 |
| Opus 5 | $0.00059 | $0.02158 |
| Sonnet 5 | $0.00024 | $0.00863 |
| Haiku 4.5 | $0.00012 | $0.00432 |
Grade A, and why
agentic-responsible-ai-assessment 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 — 372 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentic Responsible AI Assessment
When to Apply
Reference this skill when the user asks to:
- Run a Responsible AI assessment or RAI scorecard for an agentic system.
- Perform an agentic AI maturity review across governance, safety, and fairness.
- Evaluate an agent platform's governance / safety / fairness posture and see it charted across the eight RAI dimensions.
Disclaimer
Display this disclaimer verbatim to the client at the start of every assessment, before the first question:
This skill helps you assess your Responsible AI posture. Note however, that it is not comprehensive and even perfect scoring does not ensure you are compliant with any legal obligations. Responsible AI practices vary by industry, please also consult industry-specific guidances and the Responsible AI Well-Architected Lens.
Overview
Guide a client through a structured Responsible AI assessment for agentic systems. The skill asks 20 questions across three phases (Governance Foundation → Pilot Deployment → Evaluation and Hardening), scores each answer 0–5 against a maturity rubric, and renders a live posture bar chart across eight RAI dimensions after every answer.
You are a Responsible AI assessor. You guide a client, one question at a time,
through the questionnaire in references/questionnaire.md, score each answer against the
0–5 rubric, and after every question you render a posture bar chart across
all eight Responsible AI dimensions.
This skill is UI-adaptive. It first detects which client it is running in, then picks the richest visualization that client can actually render:
- Amazon Quick → Highcharts HTML artifact. Quick does not render
Mermaid inline (it shows as a dead code block), but it does render live HTML.
Emit an
<artifact type="html">column chart using the bundled Highcharts library. This is the preferred rich mode when running in Quick. - Other desktop / IDE clients that render Markdown + Mermaid (Kiro desktop, Claude Desktop, GitHub Copilot Chat in VS Code) → Mermaid bar chart so the client draws a real graphic.
- Terminal clients that only do syntax-highlighted text (Kiro-CLI, Claude Code, any SSH/CI shell) → ASCII bar chart.
What ships with it
2 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.
- 12d ago First seen · 372 lines · 118 tokens per session scan A 60779d68d323
agentic-responsible-ai-assessment is a skill published in the GitHub repository aws-samples/sample-agent-skills-for-builders (47 stars, last pushed 16d ago), licensed Apache-2.0. It adds 118 tokens to every session and 4,315 once invoked, about $0.0006 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
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…