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Found 9,733 Skills
Sector rotation continuous monitoring via Longbridge — 6–12 month trend tracking across economic cycles (recovery / overheating / stagflation / recession), identifies leading sectors per cycle phase (recovery→consumer discretionary/financials, overheating→energy/materials, stagflation→healthcare/staples, recession→utilities/bonds), and outputs sector allocation recommendations. Differs from longbridge-sector-rotation which gives a point-in-time snapshot. Triggers: "行业监控", "板块监控", "行业跟踪", "经济周期", "顺周期", "逆周期", "行业配置", "周期行业", "防御行业", "行业仓位", "行業監控", "板塊監控", "行業追蹤", "經濟週期", "順週期", "逆週期", "行業配置", "週期行業", "防禦行業", "sector monitor", "sector tracking", "economic cycle", "defensive sector", "cyclical sector", "sector allocation", "late cycle", "early cycle", "sector positioning".
Generate, remix, and manage short video clips via OpenAI's Sora API. Useful for cinematic shots, b-roll, and rapid concept video iteration.
DeepEval evaluation workflow for AI agents and LLM applications. TRIGGER when the user wants to evaluate or improve an AI agent, tool-using workflow, multi-turn chatbot, RAG pipeline, or LLM app; add evals; generate datasets or goldens; use deepeval generate; use deepeval test run; add tracing or @observe; send results to Confident AI; monitor production; run online evals; inspect traces; or iterate on prompts, tools, retrieval, or agent behavior from eval failures. AI agents are the primary use case. Covers Python SDK, pytest eval suites, CLI generation, tracing, Confident AI reporting, and agent-driven improvement loops. DO NOT TRIGGER for unrelated generic pytest, non-AI test setup, or non-DeepEval observability work unless the user asks to compare or migrate to DeepEval.
/cs:cto-review <plan> — Architecture and scaling interrogation. Tech debt, scaling cliffs, team scaling, build-vs-buy.
Swiss-grid fintech deck template in black / warm paper / neon-lime contrast. Use when users ask for premium data-story slides with strict modular layout, bold numeric cards, restrained motion, and keyboard/click navigation in one HTML file.
Run Claude Code CLI, VS Code, or JetBrains ACP through a local proxy that routes to NVIDIA NIM, Kimi, OpenRouter, DeepSeek, or local LLMs
Local proxy that lets OpenAI Codex CLI/desktop talk to MiMo, DeepSeek, and other LLMs via Responses API translation
Interactive setup guide for using Infisical as a secret management tool in your projects. Helps users integrate Infisical into local development (CLI), Docker containers (build-time and runtime secret injection), CI/CD pipelines (GitHub Actions, GitLab CI), Kubernetes (Operator + CRDs), and application code (Node.js, Python, Go, Java, .NET, Ruby SDKs). Also walks through choosing and configuring machine identity auth methods (Universal Auth, AWS Auth, Kubernetes Auth, OIDC, etc.). Use this skill whenever someone asks about: using Infisical, injecting secrets, infisical run, infisical init, connecting their app to Infisical, Docker secrets, Kubernetes secrets operator, machine identity setup, SDK initialization, CI/CD secret injection, or 'how do I get my secrets into my app'.
Required reading before writing any HogQL/SQL or calling execute-sql against PostHog. Use whenever the user wants to search, find, or do complex aggregations PostHog entities (insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, data warehouse, persons, etc.) and query analytics data (trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, LLM traces). Covers HogQL syntax differences from ClickHouse SQL, system table schemas (system.*), available functions, query examples, and the schema-discovery workflow.
Expert guidance for developing with the tinystruct Java framework. Use when working on the tinystruct codebase or any project built on tinystruct — including creating Application classes, @Action-mapped routes, unit tests, ActionRegistry, HTTP/CLI dual-mode handling, the built-in HTTP server, the event system, JSON with Builder/Builders, database persistence with AbstractData, POJO generation, Server-Sent Events (SSE), file uploads, and outbound HTTP networking.
Architect, build, and debug Kafka Streams apps (JVM-embedded stream processing). Use when user mentions KStream, KTable, topology, TopologyTestDriver, StreamsBuilder, interactive queries, GlobalKTable, joins/windows/aggregations, or debugging issues (rebalancing, state stores, lag, deserialization errors). Also use when user wants to optimize Kafka Streams for WarpStream or tune Kafka Streams client configuration for WarpStream. Do NOT trigger for Flink, connectors, CDC, or plain producer/consumer.
cuOpt REST server — what it does and how requests flow. Domain concepts; no deploy or client code.