「content moderation」の検索結果

Use when setting up CMS workspaces, creating or publishing content types for Experience Cloud sites, managing content scheduling, or configuring audience targeting on content variants. Triggers: 'set up CMS workspace', 'publish content to Experience Cloud site', 'content scheduling community', 'audience targeting content', 'managed content vs unmanaged', 'custom content type metadata', 'CMS channel configuration'. NOT for moderating member-posted content — use admin/experience-cloud-moderation. NOT for Knowledge vs an external CMS or CMS Connect — use architect/knowledge-vs-external-cms.

日本語の概要は準備中です。原文の説明を表示しています。

Set up or tune Experience Cloud content moderation: keyword/criteria rules, member reputation system, moderation queue. Triggers: 'set up community content moderation', 'configure reputation levels', 'flagging rules Experience Cloud', 'moderation queue setup', 'keyword blocking community', 'approve community posts before publishing'. NOT for publishing or scheduling CMS articles on the site — use admin/experience-cloud-cms-content. NOT for deciding which behaviours to reward or how to name reputation tiers — use admin/community-engagement-strategy.

日本語の概要は準備中です。原文の説明を表示しています。

Azure AI Content Safety SDK for Java workflow skill. Use this skill when the user needs Build content moderation applications using the Azure AI Content Safety SDK for Java and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

日本語の概要は準備中です。原文の説明を表示しています。

Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification. Triggers: "azure-ai-contentsafety", "ContentSafetyClient", "content moderation", "harmful content", "text analysis", "image analysis".

日本語の概要は準備中です。原文の説明を表示しています。

Azure AI Content Safety SDK for Java workflow skill. Use this skill when the user needs Build content moderation applications using the Azure AI Content Safety SDK for Java and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

日本語の概要は準備中です。原文の説明を表示しています。

Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification. Triggers: "azure-ai-contentsafety", "ContentSafetyClient", "content moderation", "harmful content", "text analysis", "image analysis".

日本語の概要は準備中です。原文の説明を表示しています。

Implement comprehensive safety guardrails for LLM applications including content moderation (OpenAI Moderation API), jailbreak prevention, prompt injection defense, PII detection, topic guardrails, and output validation. Essential for production AI applications handling user-generated content. Use when ", guardrails, content-moderation, prompt-injection, jailbreak-prevention, pii-detection, nemo-guardrails, openai-moderation, llama-guard, safety" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Systematically bypass LLM safety filters and content moderation systems using advanced jailbreaking techniques. Use this skill when testing AI systems for safety alignment robustness, evaluating content moderation effectiveness, or conducting authorized AI red team assessments. Covers role-play attacks, few-shot manipulation, encoding bypass, multi-modal exploitation, and automated jailbreak discovery methods.

日本語の概要は準備中です。原文の説明を表示しています。

Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.

日本語の概要は準備中です。原文の説明を表示しています。

Content moderation API integration using OpenAI Moderation, Perspective API, and others

日本語の概要は準備中です。原文の説明を表示しています。

Use when a Scenario generation is blocked, refused, or returns a moderation or sensitive-content error, when a video is rejected after rendering or its audio track is flagged, when an output is flagged for likeness to a real person or for IP and copyright detection, when the same prompt passes on one model and fails on another, or when a team's own characters, weapons, or props get flagged. Keywords: blocked prompt, content moderation, refused generation, provider filter, false positive.

日本語の概要は準備中です。原文の説明を表示しています。

Implement safety guardrails for AI systems — content filtering, prompt injection detection, output validation, bias mitigation, and responsible AI practices. Use when tasks involve adding safety layers to LLM applications, detecting prompt injection attacks, filtering harmful content, implementing rate limiting for AI APIs, validating LLM outputs against schemas, building moderation pipelines, or ensuring AI systems comply with safety policies.

日本語の概要は準備中です。原文の説明を表示しています。

Detect AI-generated text using rule-based analysis, LLM-as-judge scoring, and optional external APIs. Use when: auditing content for AI authorship, academic integrity checks, editorial review, SEO content audits.

日本語の概要は準備中です。原文の説明を表示しています。

Detects absence of a content moderation service integration for apps that accept user-uploaded media or posts, enforcing Guideline 1.2's requirement for timely response to content reports.

日本語の概要は準備中です。原文の説明を表示しています。

Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text/image analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.

日本語の概要は準備中です。原文の説明を表示しています。

Build content moderation applications using the Azure AI Content Safety SDK for Java.

日本語の概要は準備中です。原文の説明を表示しています。

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

日本語の概要は準備中です。原文の説明を表示しています。

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

日本語の概要は準備中です。原文の説明を表示しています。

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

日本語の概要は準備中です。原文の説明を表示しています。

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

日本語の概要は準備中です。原文の説明を表示しています。

Für User Content Moderation: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.

日本語の概要は準備中です。原文の説明を表示しています。

Fix silent video/media processing failures caused by URL extraction code that filters on file extensions (.mp4, .webm, .webp). Use when: (1) Media moderation, transcoding, or analysis silently skips files from Blossom or content-addressed storage servers, (2) URL extraction from Nostr event tags (imeta, r tags) drops URLs without recognized extensions, (3) CDN fallback URLs append .mp4 but the actual server uses extensionless content-addressed paths like /{sha256}. Common in Nostr video events (kind 34236) where different clients use different URL formats.

日本語の概要は準備中です。原文の説明を表示しています。

Build AI content moderation systems. TRIGGERS - Use when user needs help with ai-moderation-system related tasks.

日本語の概要は準備中です。原文の説明を表示しています。

Build AI content moderation systems. TRIGGERS - Use when user needs help with ai-content-moderator related tasks.

日本語の概要は準備中です。原文の説明を表示しています。