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Found 10,562 Skills
Smart Money analytics on OKX: leaderboard traders, position tracking, trade records, aggregated consensus signals, and signal history. Use this skill when the user asks about 聪明钱, smart money, 牛人榜, leaderboard, top traders, 带单员, lead traders, 交易员排行, trader ranking, trader positions, trader PnL, 交易员持仓, 交易员收益, smart money signal, 聪明钱信号, long/short ratio, 多空比, capital flow, 资金流向, position conviction, 仓位强度, entry price distribution, smart money overview, 聪明钱总览, signal history, 信号历史, trader search, 搜索交易员, who is trading BTC, 谁在交易BTC, recommend traders, 推荐交易员, best traders, top performers.
Generate self-contained HTML pages and slide decks (diagrams, comparison tables, architecture overviews, diff reviews, visual recaps) by emitting semantic component JSON. Use whenever a visual artifact communicates better than terminal prose — proactively trigger on 4+ row tables, ASCII flowcharts, multi-stage pipelines, or explicit "make a diagram / slides / recap" requests.
An image generation/editing Skill for GPT Image 2. It can be used in 3 environments: (A) Garden Local Mode: directly generate and save images via OpenAI-compatible APIs; (B) Host-Native Mode: treat this Skill as a prompt engineering guide, and pass the rendered prompt to the image tool built into the host Agent for image generation; (C) Advisor Mode: degrade to a high-quality prompt consultant when the host has no image tools. It covers 18 major categories and over 80 structured templates, including scenarios such as posters, UI, products, infographics, academic figures, technical architecture diagrams, comics, avatars, process boards, storyboards, IP peripherals, and editing workflows.
A valid skill used for testing frontmatter validation. Do NOT use for production workflows.
Audits AI-generated or AI-enhanced listing images against the 2026 Amazon disclosure and representation policy before submission. A 5-gate flow catches the issues that trigger suppression or a misrepresentation flag. Use when a user asks about AI image policy, AI photo rules, image suppression, or 2026 image compliance. Trigger phrases: "AI image Amazon policy", "AI generated photos listing", "image suppression AI", "Amazon AI image rules 2026". Works with zero tools.
AI agent patterns with Trigger.dev - orchestration, parallelization, routing, evaluator-optimizer, and human-in-the-loop. Use when building LLM-powered tasks that need parallel workers, approval gates, tool calling, or multi-step agent workflows.
Guide for Vercel AI SDK v6 implementation patterns including generateText, streamText, ToolLoopAgent, structured output with Output helpers, useChat hook, tool calling, embeddings, middleware, and MCP integration. Use when implementing AI chat interfaces, streaming responses, agentic applications, tool/function calling, text embeddings, workflow patterns, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, agent development, or tool calling tasks.
Use when SwiftUI view debugging requires systematic investigation - view updates not working after basic troubleshooting, intermittent UI issues, complex state dependencies, or when Self._printChanges() shows unexpected update patterns - systematic diagnostic workflows with Instruments integration
Generate declarative multi-agent systems (MAS) using POMASA pattern language. Use when building agent pipelines, orchestrating multiple AI agents, or creating research automation workflows. Supports patterns like Prompt-Defined Agent, Orchestrated Pipeline, Filesystem Data Bus, and Verifiable Data Lineage.
Create and manipulate Excel XLSX files programmatically. Use when the user needs to generate spreadsheets, modify XLSX templates, extract spreadsheet content, or automate Excel workflows. Supports both template-based generation (for branding compliance) and from-scratch creation. Keywords: Excel, XLSX, spreadsheet, workbook, worksheet, data, report, template, financial, analysis.
Complete E2E (end-to-end) and integration testing skill for TypeScript/NestJS projects using Jest, real infrastructure via Docker, and GWT pattern. ALWAYS use this skill when user needs to: **SETUP** - Initialize or configure E2E testing infrastructure: - Set up E2E testing for a new project - Configure docker-compose for testing (Kafka, PostgreSQL, MongoDB, Redis) - Create jest-e2e.config.ts or E2E Jest configuration - Set up test helpers for database, Kafka, or Redis - Configure .env.e2e environment variables - Create test/e2e directory structure **WRITE** - Create or add E2E/integration tests: - Write, create, add, or generate e2e tests or integration tests - Test API endpoints, workflows, or complete features end-to-end - Test with real databases, message brokers, or external services - Test Kafka consumers/producers, event-driven workflows - Working on any file ending in .e2e-spec.ts or in test/e2e/ directory - Use GWT (Given-When-Then) pattern for tests **REVIEW** - Audit or evaluate E2E tests: - Review existing E2E tests for quality - Check test isolation and cleanup patterns - Audit GWT pattern compliance - Evaluate assertion quality and specificity - Check for anti-patterns (multiple WHEN actions, conditional assertions) **RUN** - Execute or analyze E2E test results: - Run E2E tests - Start/stop Docker infrastructure for testing - Analyze E2E test results - Verify Docker services are healthy - Interpret test output and failures **DEBUG** - Fix failing or flaky E2E tests: - Fix failing E2E tests - Debug flaky tests or test isolation issues - Troubleshoot connection errors (database, Kafka, Redis) - Fix timeout issues or async operation failures - Diagnose race conditions or state leakage - Debug Kafka message consumption issues **OPTIMIZE** - Improve E2E test performance: - Speed up slow E2E tests - Optimize Docker infrastructure startup - Replace fixed waits with smart polling - Reduce beforeEach cleanup time - Improve test parallelization where safe Keywords: e2e, end-to-end, integration test, e2e-spec.ts, test/e2e, Jest, supertest, NestJS, Kafka, Redpanda, PostgreSQL, MongoDB, Redis, docker-compose, GWT pattern, Given-When-Then, real infrastructure, test isolation, flaky test, MSW, nock, waitForMessages, fix e2e, debug e2e, run e2e, review e2e, optimize e2e, setup e2e
Complete workflow for implementing Mapbox search in applications - from discovery questions to production-ready integration with best practices