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Provides a structured template for creating hands-on exercises in a Physical AI textbook, covering exercise types (thought experiment, simulation, hardware integration, capstone) and a progressive difficulty curve. Useful for designing educational activities with clear validation criteria and hardware notes.

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Screening for psychological distress with K6 and K10 scales, including scoring and interpretation guidance.

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Detects AI-generated Russian text and rewrites it to sound natural on user request. Focuses on removing machine-like patterns without changing meaning.

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Analyze content for search engine and AI discoverability. Evaluate titles, meta descriptions, headings, and AEO patterns for new or existing content.

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Draft or revise X, LinkedIn, and Bluesky social copy in a blog post's frontmatter, looping with self-critique until it passes review.

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Analyzes legal texts in plain language: checks deadlines, form, jurisdiction, and urgent measures; provides a risk traffic light and immediate actions.

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Guidance for writing notifications and alerts: calibrate urgency, choose the right component (toast, banner, modal), and craft messages that inform without overwhelming.

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Game design principles. GDD structure, balancing, player psychology, progression.

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Adds pedagogical markdown to Jupyter notebooks: interpretations, transitions, and conclusions, with optional execution and error fixing.

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Teaches users given materials, diagnoses learning ability, and mimics teaching styles.

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Always-on autonomous meme dropper. Fires 1-3 image+sound combos and 1-5 sound-only per response, scaled to response length.

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Checks deadlines, form, jurisdiction, legal remedy and immediate measures for legal texts; provides a traffic-light risk assessment with immediate steps.