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Found 567 Skills
Read your database schema, generate behavioral user segments with exact queries, and recommend targeted actions per segment. Use when the user wants to understand their user base, find power users, identify churn risk, build email cohorts, or understand usage patterns. Triggers on requests like "segment users", "who are my power users", "find churned users", "user cohorts", "churn analysis", "inactive users", "behavioral segmentation", "who's about to leave", or any mention of grouping users by activity, usage, or lifecycle.
Convert between XNO units (raw/xno/knano/mnano) with exact BigInt precision.
Use this skill when crafting LLM prompts, implementing chain-of-thought reasoning, designing few-shot examples, building RAG pipelines, or optimizing prompt performance. Triggers on prompt design, system prompts, few-shot learning, chain-of-thought, prompt chaining, RAG, retrieval-augmented generation, prompt templates, structured output, and any task requiring effective LLM interaction patterns.
Use this skill when creating conference talks, live coding demos, technical blog posts, SDK quickstart examples, or community engagement strategies. Triggers on developer relations, DevRel, developer experience, tech evangelism, talk proposals, CFP submissions, demo scripts, tutorial writing, hackathon planning, community building, and any task involving advocating a product or API to a developer audience.
Prevents premature execution on ambiguous requests. Analyzes request clarity using 5W1H decomposition, surfaces hidden assumptions, and generates structured clarifying questions before work begins. Use at the start of any non-trivial task, or when a request could be interpreted multiple ways. Triggers on "뭘 원하는건지", "요구사항 정리", "clarify", "what exactly", "scope", "requirements", "정확히 뭘", "before we start".
Flutter state management patterns — decision tree for setState, Provider, Riverpod, and BLoC with concrete examples and testing strategies
Produces API reference documentation for Next.js APIs: functions, components, file conventions, directives, and config options. **Auto-activation:** User asks to write, create, or draft an API reference page. Also triggers on paths like `docs/01-app/03-api-reference/`, or keywords like "API reference", "props", "parameters", "returns", "signature". **Input sources:** Next.js source code, existing API reference pages, or user-provided specifications. **Output type:** A markdown (.mdx) API reference page with YAML frontmatter, usage example, reference section, behavior notes, and examples.
Generates technical guides that teach real-world use cases through progressive examples. **Auto-activation:** User asks to write, create, or draft a guide or tutorial. Also use when converting feature documentation, API references, or skill knowledge into step-by-step learning content. **Input sources:** Feature skills, API documentation, existing code examples, or user-provided specifications. **Output type:** A markdown guide with YAML frontmatter, introduction, 2-4 progressive steps, and next steps section.
Write Milvus application-level Jupyter notebook examples using a Markdown-first workflow with jupyter-switch for format conversion.
Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki"
Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"
Use this skill when building real-time data pipelines, stream processing jobs, or change data capture systems. Triggers on tasks involving Apache Kafka (producers, consumers, topics, partitions, consumer groups, Connect, Streams), Apache Flink (DataStream API, windowing, checkpointing, stateful processing), event sourcing implementations, CDC with Debezium, stream processing patterns (windowing, watermarks, exactly-once semantics), and any pipeline that processes unbounded data in motion rather than data at rest.