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Guardrails

Checked
fusengine·vlatest·other·MIT

Guardrails helps refine outputs by setting constraints & boundaries, ensuring responses align with desired tones and topics for safer, more focused content.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add fusengine/agents --skill guardrails -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

fusengine

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned fusengine/agents at 980930ea9c.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
980930ea9c
Manifest
plugins/prompt-engineer/skills/guardrails/SKILL.md
Scanned
3 files, 376 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The guardrails skill provides a mechanism to constrain AI agent behavior and output. It allows you to define rules and boundaries, preventing the agent from generating harmful or inappropriate responses. This skill helps ensure responsible and safe interactions with your AI agents by enforcing predefined limitations on their actions.

When to use it

  • Content Moderation: When building an agent that generates text content (e.g., a chatbot) and you need to prevent offensive language or sensitive topics.
  • Data Privacy: To restrict the agent from revealing personally identifiable information (PII) during conversations.
  • Task Boundaries: When defining specific tasks for an agent, guardrails can ensure it stays within those boundaries and doesn't deviate into unrelated areas.
  • Brand Safety: To prevent the agent from making statements that could damage your brand reputation or violate legal guidelines.

Key capabilities

  • Rule definition: Allows users to define rules for acceptable behavior.
  • Content filtering: Filters generated content based on defined rules.
  • Behavioral constraints: Restricts actions and responses of the AI agent.
  • Safety enforcement: Enforces safety protocols within the agent's interactions.

Example prompts

  • "Implement a rule to prevent the agent from discussing politics."
  • "Configure guardrails to block any response containing profanity."
  • "Set up rules to ensure the agent doesn’t share personal information about users.”

Tips & gotchas

The effectiveness of guardrails depends on well-defined and comprehensive rules. Start with a small set of critical rules and iteratively refine them as you observe the agent's behavior.