Knowledge base from "Learning Spark, 2nd Edition" by Damji, Wenig, Das & Lee. Use when working with Apache Spark / PySpark, preparing for the Databricks Certified Associate Developer for Apache Spark exam, or applying the authors' frameworks for Spark architecture, DataFrame API, Spark SQL, Structured Streaming…
The catalog agent is the knowledge hub of the Data Workers swarm. It crawls, indexes, and serves metadata about every data asset across an organization's stack — tables, views, models, pipelines, dashboards, and metrics. It provides natural-language search, column-level lineage, quality scoring, and automated…
Use this skill for ANY coding question involving LangChain products (LangChain, LangGraph, LangSmith SDK). Covers agent development patterns, primitives, context management, multi-agent systems, and when to use createagent vs createdeepagent vs raw LangGraph. Consult this BEFORE writing any LangChain-related code.
Build a custom source → raw-intake adapter for Athenaeum. Use when someone wants to feed an external source (an API, an export file, a message feed, a scraper, another tool's output) into an Athenaeum knowledge base, asks "how do I write an adapter / integration for athenaeum", or wants to turn some data source into…
A sidecar skill that lets text-only models work from images and office documents through Groq's vision service. It converts PNG, JPG, PDF, PPTX, and DOCX files into Traditional Chinese Markdown descriptions, including extracted text.
Use the openrouter CLI to call any OpenRouter API endpoint from the shell - chat / messages / responses (with web search, PDF input, prompt caching, reasoning budgets, tools), embeddings, rerank, text-to-speech, speech-to-text, image + video generation, model + provider discovery, generation lookup, credits, activity…
A skill for writing and improving prompts for Seedance 2.5, a video-generation system. It covers text-to-video, image-to-video, editing, video extension, references, camera movement, green-screen work, sound, and lip sync.
An image-annotation workflow for creating COCO detection and instance-segmentation labels for selected object categories in one image. COCO is a common format for training and evaluating computer-vision models.
Use when generating images with Midjourney, constructing MJ prompts, iterating on MJ output quality, choosing between --sref/--oref/style codes, scoring image results, or building reusable prompt patterns. Also use when exploring MJ style codes, animating images, or debugging why a prompt isn't producing the intended…
Export Claude Code and Codex conversation history to Hugging Face as structured training data. Use when the user asks about exporting conversations, uploading to Hugging Face, configuring codeclaw, reviewing PII/secrets in exports, or managing their dataset.
Discover proven Outcomes and turn a rough request into one complete execution prompt for a fresh agent. Also author and validate source-owned Outcomes for Possible.
An image-understanding bridge for local AI systems that cannot read or interpret pictures. It sends images to DeepSeek’s vision mode and returns a text answer.
Optimizes prompts using full GEPA methodology (Genetic-Pareto Evolution). Use when user wants to improve a prompt's accuracy on test cases, mentions "optimize prompt", "improve prompt", or has examples of desired input/output pairs. Implements Pareto frontier selection, trace-based reflection, and crossover mutations.
Run a single prompt across multiple LLMs in parallel via OpenRouter, then synthesize their responses into one answer with a judge model. Use when the user wants multi-model fusion, ensemble LLM queries, parallel model comparison, or a second opinion across providers.
Run or adapt dynamo preprocessing with dynamo.preprocessing.Preprocessor, including the recipe branches monocle, seurat, sctransform, pearsonresiduals, and monoclepearsonresiduals. Use when converting or reproducing docs/tutorials/notebooks/100tutorialpreprocess.ipynb, preprocessing an AnnData object for downstream…
Creates detailed English natural-language image prompts for NSFW scenes, including nudity, erotic clothing, solo play, sex toys, partnered intercourse, oral/manual/body stimulation, multi-participant compositions, exhibitionism, bondage, rough play, fluids, fantasy partners, and explicitly requested restricted or…
Write, optimize, review, and structure prompts for AI assistants (Claude, ChatGPT, Codex, Claude Code, agents). Use this skill whenever the user asks to write a prompt, optimize a prompt, fix/improve a prompt, review a prompt, turn a vague request into a reusable prompt, design system prompts / task instructions for…
Explain the Phoenix ML model architecture for X recommendations. Use when users ask about embeddings, transformers, how predictions work, or ML model details.
Inference-time system-prompt rules for Korean multi-turn RAG agents. Hard imperatives + Korean few-shots + decision tables for ambiguous phrasings — followup handling, persistent-filter durability, particle stripping, verifier cross-turn context, hedge-phrase suppression, LLM-over-regex routing. Distilled from Korean…
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