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Claude Opus 4.1 Multimodal Analysis Skill

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Linked challenge: Real-time Multimodal Misinformation Shield

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Linked challenge

Real-time Multimodal Misinformation Shield

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Implement a Semantic Kernel skill that leverages Claude Opus 4.1 to analyze a multimodal social media post. This skill should take text, an image URL, and a video frame URL as input and output a judgment on whether the content violates specific (simulated) platform policies, providing a reason and confidence score.

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Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

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Update libraries, interfaces, and environment assumptions to match the stack you actually run.

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Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

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Purpose

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This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Real-time Multimodal Misinformation Shield

In light of growing concerns over misinformation on social media platforms and the potential for malicious deepfakes, this challenge focuses on developing a cutting-edge, real-time AI assistant for content moderation and misinformation detection. The system will monitor a simulated social media feed, identify multimodal content (text, image, video frames) that violates platform policies or spreads misinformation, and provide immediate alerts or suggested counter-narratives. This challenge emphasizes the integration of advanced multimodal LLMs like Claude Opus 4.5, a voice interface for rapid human intervention, and robust memory management for policy enforcement. The assistant must operate in near real-time, making accurate assessments of complex, often ambiguous, content and providing explainable justifications for its decisions.

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