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Found 539 Skills
Intelligent music genre search assistant with 5947 genres sourced from RateYourMusic. It supports quick lookup, smart recommendations, and hierarchical exploration. USE THIS SKILL when users mention: - Explicit commands: /genre, /music-style, "query music genre", "recommend music style" - Creation needs: "I want to make a song/music in XX style", "help me choose a music style", "what style is suitable for XX scenario", "recommend some music styles with XX characteristics" (e.g., suitable for late night, energetic, ethereal, dark) - Exploration: "What subgenres does XX style have", "What's under Ambient", "Show me the branches of Rock" - Suno music generation: Trigger this skill before using the suno-music-creator skill when the genre needs to be determined, or when the user says "generate with Suno" but hasn't specified a genre
Specialized feature development agents. Use for deep codebase exploration and architecture design during feature development.
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
Context-driven aesthetic exploration with anti-cliche validation: typography, color, animation, atmosphere. Use when starting a frontend needing distinctive aesthetics, refreshing generic designs, or auditing for "AI slop" patterns. Use for "distinctive frontend", "unique aesthetics", "avoid generic design", "creative frontend". Do NOT use for quick prototypes, strict brand compliance, backend projects, or data visualization.
Apply organizational ambidexterity theory to balance exploration and exploitation activities. Use this skill when the user needs to diagnose whether an organization is over-exploiting or over-exploring, design structures that support both innovation and efficiency, or evaluate the tension between short-term performance and long-term renewal.
Conduct a targeted code exploration of the repository, and document the process of "Ask Questions → Read Code → Draw Conclusions" as searchable evidence for direct reuse when similar questions arise next time. There are three types: question (investigate code around a specific question and provide conclusions), module-overview (sort out the structure, boundaries, entry points, and dependencies of a module), and spike (conduct lightweight technical exploration of multiple possible directions without making final decisions). Trigger scenarios: Users say "Let's explore first", "How is X implemented in this repository", "Quickly get familiar with this module", "Archive the exploration results". Refer to `codestable/reference/system-overview.md` for how to distinguish it from learning / tricks / decisions.
Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
Comprehensive academic writing skill for drafting journal-ready manuscripts. Orchestrates specialized sub-skills for introduction sections (q-intro), descriptive analysis (q-descriptive-analysis), methods sections (q-methods), and results sections (q-results). Use when the user needs end-to-end support for academic manuscript preparation, from initial data exploration through publication-ready prose. Follows APA 7th edition formatting standards.
LLM integration patterns for function calling, streaming responses, local inference with Ollama, and fine-tuning customization. Use when implementing tool use, SSE streaming, local model deployment, LoRA/QLoRA fine-tuning, or multi-provider LLM APIs.
Databricks CLI operations: auth, profiles, Unity Catalog, data exploration, jobs, pipelines, clusters, model serving, bundles and more. Contains up-to-date guidelines for all Databricks CLI tasks, useful for all Databricks-related tasks.
Best practices for doing quick exploratory data analysis with minimal code and a Pandas .plot like API using HoloViews hvPlot.