Individual skill
llm-guardrails-spec
Specify the safety and reliability guardrails for an LLM feature before it ships. Use when asked to define LLM guardrails, add safety controls to an AI feature, prevent prompt injection or jailbreaks, or harden a chatbot/agent against misuse. Produces a guardrails spec — threats, input/output controls, refusal and escalation policy, logging, and a red-team test set — mapped to where each control runs.
skills/llm-guardrails-spec/SKILL.md
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- Last checked
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SKILL.mdcore · 4,635 bytes
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# LLM Guardrails Spec Skill
An LLM feature without guardrails fails in public: it leaks data, follows an injected instruction, answers
out of scope, or says something the brand can't stand behind. This skill specifies the controls that prevent
that — what to block, where to block it (input, model, output, or human), and how you'll prove it works — so
safety is a reviewable spec, not a hope.
## Working from a brief
Given "we're adding an AI chat to our support site", **produce the full guardrails spec anyway** — infer the
threat surface from the feature type, label assumptions, and flag what to confirm. Never hand back only a list
of risks with no controls; the controls and their placement are the deliverable.
## Required Inputs