Skip to content
TrustedSkillsbeta
Back to all skills

Azure Ai Contentsafety Py

Checked
sickn33·vlatest·cloud·MIT

Helps with Azure, AI as part of deploying and managing cloud infrastructure workflows.

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 sickn33/agentic-awesome-skills --skill azure-ai-contentsafety-py -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

sickn33

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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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

Commit
5a4cdd9df8
Manifest
skills/azure-ai-contentsafety-py/SKILL.md
Scanned
1 file, 201 lines
Copies in repo
3 — all of them scanned
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

This skill leverages the Azure AI Content Safety client library for Python. It allows you to programmatically analyze text content and automatically detect potentially harmful or offensive material, such as hate speech, sexually suggestive content, self-harm threats, and violence. The analysis returns a detailed report with confidence scores for each category of potential violation.

When to use it

  • Content Moderation: Automatically flag user-generated content on forums, social media platforms, or review sites before human moderation.
  • Chatbot Safety: Integrate into chatbots to prevent them from generating inappropriate responses and ensure a safe user experience.
  • Code Generation Security: Analyze code snippets generated by AI models for potential vulnerabilities or harmful instructions.
  • Automated Document Review: Scan documents for sensitive content before distribution or publication, ensuring compliance with internal policies.

Key capabilities

  • Text classification across multiple categories (hate speech, sexually suggestive content, self-harm, violence, etc.)
  • Confidence scores for each category to assess the severity of potential violations.
  • Detailed reports providing insights into why a piece of content was flagged.
  • Python client library for easy integration with existing Python workflows.

Example prompts

  • "Analyze this text: 'This is an example sentence.'"
  • "Check this user comment for any harmful language: [user comment]"
  • "Can you assess the safety risk of this generated code snippet?"

Tips & gotchas

  • Requires an Azure subscription and access to the AI Content Safety service. You'll need your endpoint key and deployment name.
  • The accuracy of content detection depends on the quality and context of the input text.