
guardrail-design
Defining behavioral boundaries — what the AI should and shouldn't do.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owl-listener/ai-design-skills --skill guardrail-design- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads guardrail-design automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Guardrail Design
Guardrails are the behavioral boundaries that define what an AI product will and won't do. They're not just safety constraints — they're design decisions that shape the entire user experience.
Types of Guardrails
- Content guardrails: What topics the AI will and won't discuss. What it generates and refuses to generate.
- Action guardrails: What the AI can do in the world — send emails, make purchases, delete data — and what requires human approval.
- Tone guardrails: How the AI communicates — what language it uses, how formal or casual, when it's direct vs. diplomatic.
- Scope guardrails: What the AI considers in and out of scope for its role. A coding assistant shouldn't give medical advice.
- Confidence guardrails: When the AI should express uncertainty, hedge, or refuse rather than guessing.
Designing Guardrails as Product Decisions
Every guardrail is a product decision with tradeoffs:
- Too strict: The product feels limited, frustrating, and paternalistic. Users route around the guardrails.
- Too loose: The product causes harm, loses trust, and creates liability.
- Inconsistent: Users can't predict what the AI will and won't do, eroding trust. The goal is guardrails that feel like good judgment, not arbitrary restrictions.
Guardrail Specification
For each guardrail, define:
- What it prevents: The specific behavior or output being constrained
- Why it exists: The harm it prevents or the value it protects
- How it manifests: What the user sees when the guardrail activates (refusal message, alternative suggestion, escalation)
- Edge cases: Grey areas where the guardrail might be too strict or too loose
- Override conditions: Whether and how the guardrail can be relaxed (admin settings, user confirmation, context-dependent)
Guardrail Communication
How the AI communicates a guardrail matters as much as the guardrail itself:
- Transparent refusal: "I can't help with that because..." — honest about the boundary
- Redirective refusal: "I can't do X, but I can help you with Y" — offering alternatives
- Silent guardrail: The AI steers away from the boundary without mentioning it
- Escalation: "This needs a human to review" — handing off rather than refusing
Design Artefacts
- Guardrail specification table: Category | Rule | Rationale | User Experience | Edge Cases
- Refusal message templates per guardrail type
- Guardrail severity tiers (hard block vs. soft warning vs. nudge)
- Testing scenarios for each guardrail
FAQ
What does the guardrail-design skill do?
Defining behavioral boundaries — what the AI should and shouldn't do.
How do I install guardrail-design?
Run npx skills add https://github.com/owl-listener/ai-design-skills --skill guardrail-design in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/guardrail-design/ (personal) or .claude/skills/guardrail-design/ (project).
Which AI agents can use guardrail-design?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is guardrail-design safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains guardrail-design?
It is published by owl-listener in owl-listener/ai-design-skills. It has 392 recorded installs.
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