AI Guardrails
Add safety layers to AI applications — input validation, prompt injection detection, output filtering, content moderation, and policy enforcement. Prevent misuse without breaking legitimate use cases.
Overview
The AI Guardrails skill, part of the TerminalSkills/skills repository, provides a structured framework for enhancing the safety and reliability of artificial intelligence applications. This security-focused tool enables developers to integrate multiple defensive layers, including input validation and prompt injection detection, to mitigate common vulnerabilities. By utilizing this skill, agents like Codex, Claude, and Gemini can perform real-time content moderation and output filtering to ensure compliance with established organizational policies. The repository, which has gained 71 stars, offers these capabilities as a Python-based solution for managing API interactions. It focuses on preventing malicious misuse while maintaining the functionality required for legitimate user requests, effectively balancing strict security enforcement with application usability across various supported AI platforms.
Use Cases
Install Notes
# Review source first
open https://github.com/TerminalSkills/skills/blob/main/skills/ai-guardrails/SKILL.mdCopy or clone the skill folder into your agent skills directory after reviewing its instructions and scripts.
Security Notes
AI Guardrails acts as a defensive middleware layer; however, users should ensure that the underlying Python environment and API keys are properly secured. While it mitigates prompt injection and unauthorized output, it should be part of a broader defense-in-depth strategy within the TerminalSkills/skills ecosystem.
Related Skills
Security And Hardening
addyosmani/agent-skills
Hardens code against vulnerabilities. Use when auditing an input handler for vulnerabilities, when handling user input, authentication, data storage, or external integrations, or when checking a login flow is safe against the OWASP Top Ten. Use when building any feature that accepts untrusted data, manages user sess...
Genotoxic
trailofbits/skills
Graph-informed mutation testing triage. Parses codebases with Trailmark, runs mutation testing and necessist, then uses survived mutants, unnecessary test statements, and call graph data to identify false positives, missing test coverage, and fuzzing targets. Use when triaging survived mutants, analyzing mutation te...
Variant Analysis
trailofbits/skills
Hunts for the other instances of a bug already found — the variants of one root cause across a codebase. Use immediately after a vulnerability, logic bug, or bad pattern turns up in a specific file and the question becomes where else it occurs, including the bare conversational form ("are there others like this?", "...
Ossfuzz
trailofbits/skills
Enrolls a project in OSS-Fuzz, Google's free continuous fuzzing service for open source, and drives it locally. Covers project.yaml, Dockerfile and build.sh setup, the helper scripts, reproducing OSS-Fuzz crash reports, and the acceptance criteria. Use when setting up continuous fuzzing for an open-source project, r...
Fuzzing Obstacles
trailofbits/skills
Patches past the barriers that stop a fuzzer making progress — checksum and hash verification, magic-value validation, time-based seeds, and other non-deterministic global state. Covers locating the blocking check, neutering it behind a fuzzing build flag, and avoiding the false positives a patch can introduce. Use...
Supply Chain Risk Auditor
trailofbits/skills
Audits a project's dependencies for supply-chain risk: version-matched advisories for direct dependencies and the full lockfile tree, abandoned or archived upstreams, npm publisher concentration, and install-time script execution. Use when asked to audit dependencies, assess supply-chain or third-party package risk,...