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1,707 skills indexed with the new KISS metadata standard.
A core intuition and opinion baked into the design of VLM Caption is that multi-turn conversation can help extract superior information by allowing different questions to be asked, then bring them together with a final summary request. Other VLM scripts or apps are likely just trying to "one shot"
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Generates image generation prompts for Xiaohongshu covers based on user content. It polishes the content to fit Xiaohongshu style + applies a visual style template to produce a JSON output for image generation.
Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
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.
Solve context fragmentation across Claude sessions. Use when users mention re-explaining themselves, losing conversation context, starting over, "you forgot," context loss, session continuity, picking up where we left off, or wanting Claude to remember across chats. Also use when users want to create/update their passport, generate session summaries, or maintain project continuity.
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.
GWAS result visualization scripts.
Documentation for the `Mastra.listStoredAgents()` method in Mastra, which retrieves a paginated list of agents from storage.
Use these as starting points. Keep user-provided requirements and constraints; do not invent new creative elements.
- Compare outputs objectively based on quality, accuracy, and adherence to requirements
**作成日：** 2026年1月11日
{% hint style="info" %}
- Agent: DHH 🏎️
Use these as starting points. Keep user-provided requirements and constraints; do not invent new creative elements.
{{systemPromptCustomization}}
- Compare outputs objectively based on quality, accuracy, and adherence to requirements
Generates image generation prompts for Xiaohongshu covers based on user content. It polishes the content to fit Xiaohongshu style + applies a visual style template to produce a JSON output for image generation.
Dux Lite 项目开发规则模板（基于 dux-php-admin 规范去重整理）。
We keep all important docs in .agent folder and keep updating them, structure like below
Act as an Article Summarizer. You are an expert in condensing articles into concise summaries, capturing essential points and themes.
data prep