Loading...
Loading...
Found 1,066 Skills
한글(HWP/HWPX) 문서를 다양한 포맷(Text, HTML, ODT, PDF)으로 변환하고, Markdown/HTML을 HWPX로 생성하는 작업을 도와줍니다. LLM/RAG 파이프라인을 위한 문서 처리, 청킹, LangChain 연동을 지원합니다.
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate exte...
Interactive tutorial teaching Snowflake Cortex CLASSIFY_TEXT for categorizing unstructured text. Guide users through classifying customer reviews using Python and SQL. Use when user wants to learn text classification, Cortex LLM functions, or analyze unstructured feedback data.
Execute a task with sub-agent implementation and LLM-as-a-judge verification with automatic retry loop
Data format specialist covering TOON encoding, JSON/YAML optimization, serialization patterns, and data validation for modern applications. Use when optimizing data for LLM transmission, implementing high-performance serialization, validating data schemas, or converting between data formats.
Convert GitHub/GitLab/Gitee repositories into comprehensive OpenCode Skills using embedded LLM calls with multiple mirrors and rate limit handling
Use when building a custom provider integration on top of @prefactor/core so your app can instrument agent, llm, and tool workflows without relying on a prebuilt adapter package.
Update the llms.txt file in the root folder to reflect changes in documentation or specifications following the llms.txt specification at https://llmstxt.org/
AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
Real-time investment context from Primary Logic — LLM-ranked relevance and impact signals from podcasts, articles, X/Twitter, Kalshi, Polymarket, earnings calls, filings, and other monitored sources across public and private companies.
Step-by-step guide for adding support for a new LLM in Dust. Use when adding a new model, or updating a previous one.
A skill for improving prompts by applying general LLM/agent best practices. When the user provides a prompt, this skill outputs an improved version, identifies missing information, and provides specific improvement points. Use when the user asks to "improve this prompt", "review this prompt", or "make this prompt better".