Azure AI Content Safety SDK for Python
Detect harmful content with Azure AI Content Safety
User-generated and AI-generated content can contain harmful material that violates community guidelines. This skill helps you automatically detect hate speech, self-harm content, sexual content, and violence with configurable severity thresholds.
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Verwendung von "Azure AI Content Safety SDK for Python". Text containing mild profanity but no hate speech
Erwartetes Ergebnis:
Hate: severity 0 (Safe), SelfHarm: severity 0 (Safe), Sexual: severity 0 (Safe), Violence: severity 0 (Safe)
Verwendung von "Azure AI Content Safety SDK for Python". Image containing weapons or violent imagery
Erwartetes Ergebnis:
Violence: severity 4 (Medium), other categories: severity 0 (Safe). Content flagged for review based on threshold settings.
Verwendung von "Azure AI Content Safety SDK for Python". Text matching custom blocklist term with halt_on_blocklist_hit enabled
Erwartetes Ergebnis:
BlocklistsMatch: true. Blocked term: [TERM]. Analysis halted before AI processing. Action: reject submission.
Sicherheitsaudit
SicherThis skill contains only documentation for the Azure AI Content Safety Python SDK. Static analysis scanned 0 files with 0 security issues detected. The skill provides legitimate instructions for content moderation using Azure services with proper credential handling via environment variables. No executable code or malicious patterns found.
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Was du bauen kannst
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Probiere diese Prompts
Analyze this text for harmful content: [INSERT TEXT]. Report severity levels for hate, self-harm, sexual, and violence categories.
Create a blocklist named [BLOCKLIST_NAME] for my domain. Add these terms: [TERM1, TERM2, TERM3]. Configure text analysis to halt when blocked terms are detected.
Analyze this image for harmful visual content: [IMAGE_FILE or URL]. Use 8-severity scale and return results for all harm categories.
Build a content moderation pipeline that: 1) Checks text against custom blocklists first, 2) Analyzes remaining content with Azure AI, 3) Applies different actions based on severity thresholds (0-2: allow, 4: flag for review, 6+: block). Log all results for audit.
Bewährte Verfahren
- Set severity thresholds appropriate for your audience and platform guidelines
- Use custom blocklists for domain-specific terms that Azure AI may not recognize
- Log all analysis results for audit trails and continuous improvement of moderation policies
Vermeiden
- Do not rely solely on automated moderation for high-stakes content decisions
- Avoid using default severity thresholds without testing against your specific content types
- Do not store or log raw harmful content in analysis results for compliance reasons
Häufig gestellte Fragen
What Azure subscription do I need for Content Safety?
How do I choose between 4-level and 8-level severity?
Can I analyze content in multiple languages?
What is the difference between blocklists and AI analysis?
How do I handle false positives in content moderation?
Is API Key or Entra ID authentication more secure?
Entwicklerdetails
Autor
sickn33Lizenz
MIT
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/azure-ai-contentsafety-pyRef
main
Dateistruktur
đź“„ SKILL.md