Tell Your Story
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].
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11,965 skills indexed with the new KISS metadata standard.
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.
Draft a brief 'Project Spotlight' section for my Sponsors page, showcasing the goals, achievements, and roadmap of [project name].
Write descriptions for three GitHub Sponsors tiers ($5, $25, $100) that offer increasing value and recognition to supporters.
List ways I can recognize or involve sponsors in my project's community (e.g., special Discord roles, early feature access, private Q&A sessions).
Tools prefixed with `A2A_` are autonomous remote agents.
- Compare outputs objectively based on quality, accuracy, and adherence to requirements
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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.
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.
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.
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.
Documentation for the `Mastra.listStoredAgents()` method in Mastra, which retrieves a paginated list of agents from storage.
For this project, use minimal spacing to keep layouts compact:
⚠️ This file is intentionally minimal.
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See the [AI Agent Guidelines](./.llm/context.md) for all AI agent guidelines.
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Use these as starting points. Keep user-provided requirements and constraints; do not invent new creative elements.