ai-safety-guardrails

ai-safety-guardrails is a skill for Claude Code, Codex from varunk130/ai-ux-skill-library. It costs 63 tokens per session (2,076 once invoked), scanned A, original, MIT.

A design guide for the parts of an AI product that prevent harm and explain restrictions. It covers content moderation, bias, sensitive content, refusals, and safety notices.

In plain words
What is it for?
Designing moderation flows, refusal messages, human review points, escalation paths, safety records, and other responsible-AI interfaces.
Why use it?
It helps teams handle unsafe or restricted AI output clearly while keeping users informed about what happened and what they can do next.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Designing moderation flows, refusal messages, human review points, escalation paths, safety records, and other responsible-AI interfaces.

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Install with agentmods
npx agentmods add skills/varunk130/ai-ux-skill-library/ai-safety-guardrails
Install

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.

Any agent
npx skills add varunk130/ai-ux-skill-library --skill ai-safety-guardrails
Clone the repo
git clone --depth 1 https://github.com/varunk130/ai-ux-skill-library

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for ai-safety-guardrails

README.md
[![agentmods](https://agentmods.dev/badge/skills/varunk130/ai-ux-skill-library/ai-safety-guardrails/github.svg)](https://agentmods.dev/skills/varunk130/ai-ux-skill-library/ai-safety-guardrails)
Your own site
<a href="https://agentmods.dev/skills/varunk130/ai-ux-skill-library/ai-safety-guardrails"><img src="https://agentmods.dev/badge/skills/varunk130/ai-ux-skill-library/ai-safety-guardrails/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.

agentmods 80×15 button for ai-safety-guardrails

Your own site · 80×15
<a href="https://agentmods.dev/skills/varunk130/ai-ux-skill-library/ai-safety-guardrails"><img src="https://agentmods.dev/badge/skills/varunk130/ai-ux-skill-library/ai-safety-guardrails.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,076 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00063 $0.02076
Opus 5 $0.00032 $0.01038
Sonnet 5 $0.00013 $0.00415
Haiku 4.5 $0.00006 $0.00208

Measured 12d ago against content hash 1a3768becfd7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ai-safety-guardrails 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.

skills/ai-safety-guardrails/SKILL.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Safety Guardrails

Design the user-facing layer of AI safety - how products prevent harm, communicate restrictions, handle sensitive content, and maintain accountability. The SHIELD framework ensures safety mechanisms protect users without destroying the user experience.

Core Principle

Safety and usability are not opposites. The best safety design is invisible when everything is fine and clear when it matters. Safety should feel like a guardrail on a mountain road - you forget it's there until you need it, and when you need it, you're grateful it's solid.


The SHIELD Framework

Letter Principle Design Question
S Scope the Risks Have you mapped every way this AI could produce harm?
H Human Oversight Gates Are there human checkpoints before high-risk AI actions take effect?
I Inform on Restriction When the AI restricts output, does it explain why and what alternatives exist?
E Escalation Paths Can users challenge a restriction through a clear, fair process?
L Log Everything Is there an auditable record of safety decisions?
D Degrade Gracefully When safety mechanisms activate, does the product still provide value?

The Harm Taxonomy for AI Products

Design different safety responses for different harm types:

Harm Category Examples Severity UX Response
Misinformation Hallucinated facts, fabricated citations, false statistics High Citation requirements, confidence indicators, verification prompts
Bias amplification Stereotyping in outputs, skewed recommendations, unfair treatment High Bias detection indicators, diverse output prompts, fairness disclaimers
Privacy leakage AI revealing personal data, memorized training content Critical Input sanitization, output scanning, PII detection alerts
Harmful instructions Dangerous activities, self-harm, illegal guidance Critical Hard block + resource referral (crisis lines, safety info)
Manipulation Persuasion without disclosure, dark patterns, emotional exploitation High Transparency requirements, intent disclosure
Overreliance Users making critical decisions solely based on AI output Medium Decision-support framing, "consult a professional" nudges
Exclusion AI that works poorly for certain languages, cultures, or accessibility needs Medium Coverage transparency, alternative pathways, inclusion testing

Read the full file on GitHub · 173 lines

Changes

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.

  1. 12d ago First seen · 173 lines · 63 tokens per session scan A 1a3768becfd7

Subscribe to this mod's changes

ai-safety-guardrails is a skill published in the GitHub repository varunk130/ai-ux-skill-library (3 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 2,076 once invoked, about $0.0003 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 2026-08-31.

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