Sample prompts (copy/paste)
Use these as starting points. Keep user-provided requirements and constraints; do not invent new creative elements.
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1,785 skills indexed with the new KISS metadata standard.
Use these as starting points. Keep user-provided requirements and constraints; do not invent new creative elements.
You generate alt text for HTML `img` tags.
| 項目 | 内容 |
Tools prefixed with `A2A_` are autonomous remote agents.
- Compare outputs objectively based on quality, accuracy, and adherence to requirements
Use npm for this project.
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领域层是 Clean Architecture 的核心层,定义业务实体、业务规则和数据访问接口。该模块保持纯 Kotlin 实现,不依赖任何 Android 框架。
generic skill
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generic skill
Documentation for the `Mastra.listStoredAgents()` method in Mastra, which retrieves a paginated list of agents from storage.
Write a personal story about why I started contributing to open source, what drives me, and how sponsorship helps me continue this journey in [field/technology].
Write an announcement for my Sponsors page about a new milestone or feature in [project], encouraging new and existing sponsors to get involved.
Write a GitHub Sponsors bio for my profile that highlights my experience in [your field], the impact of my open source work, and my commitment to community growth.
Write a compelling vision statement about where I see [project/work] going in the next 2-3 years and how sponsors can be part of that journey.
Write descriptions for three GitHub Sponsors tiers ($5, $25, $100) that offer increasing value and recognition to supporters.
Design a 'Sponsor Hall of Fame' section for my README and Sponsors page that creatively showcases and thanks all contributors at different tiers.
На основе текста из истории, создай детальное описание одной сцены на английском, а затем иллюстрацию на основе описания. Используй нейтральные обозначения для людей и животных, не имена, например, "мальчик" вместо "Ваня", "женщина" вместо "Анна", "собака" вместо "Жучка", и т.п. Если в тексте больше
| 項目 | 内容 |
Tools prefixed with `A2A_` are autonomous remote agents.
- Compare outputs objectively based on quality, accuracy, and adherence to requirements
Detects and corrects Korean AI writing patterns to transform text into natural human writing. Based on scientific linguistic research (KatFishNet paper with 94.88% AUC accuracy). Analyzes 19 patterns including comma overuse, spacing rigidity, POS diversity, AI vocabulary overuse, and structural monotony. Use when humanizing Korean text from ChatGPT/Claude/Gemini or removing AI traces from Korean LLM output.