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Found 3,332 Skills
Configures Depot-managed GitHub Actions runners as a drop-in replacement for GitHub-hosted runners. Use when setting up or migrating GitHub Actions workflows to use Depot runners, choosing runner sizes (CPU/RAM), configuring runs-on labels, setting up ARM or Windows or macOS runners, troubleshooting GitHub Actions runner issues, configuring egress filtering, using Depot Cache with GitHub Actions, or running Dagger/Dependabot on Depot runners. Also use when the user mentions depot-ubuntu, depot-windows, depot-macos runner labels, or asks about faster/cheaper GitHub Actions runners.
Determine the escalation path (Researcher vs. Human) and format the appropriate handoff. Used when the fix-engine has exhausted retry attempts.
Use when Java XML-RPC API work requires contract decisions for fault signaling and interoperability, including defining XmlRpcException-based failures, replacing void returns with explicit operation results, reviewing handlers for return-code anti-patterns, and migrating DTOs from Serializable to JAXB.
Universal fallback for executing actions across 1,000+ apps when no other skill is available. Use this skill ONLY when user requests an action on an app/service not covered by other skills (e.g., Notion, Asana, Trello, HubSpot, Airtable, Linear, Monday, Zendesk, Intercom, Stripe, Shopify, QuickBooks, Zoom, Microsoft 365, Dropbox, Box, Figma, Jira, Confluence, etc.). Do NOT use if another skill already handles the service. Triggers on requests to connect to external apps, execute actions on third-party services, or when user asks "can you actually do X" for an unsupported service.
Sets up async tests with proper fixtures and mocks using pytest-asyncio patterns. Use when testing async functions, creating async fixtures, mocking async services, or handling async context managers. Covers @pytest_asyncio.fixture, AsyncMock with side_effect, async generator fixtures (yield), and testing async context managers. Works with Python async/await patterns, pytest-asyncio, and unittest.mock.AsyncMock.
Split changes into a Graphite stack with PR titles and descriptions. Use when asked to create or propose a stacked PR series.
Vapor UI design system component and icon guide, UI mockup generator, and Figma design converter. Provides component catalog, icon lookup, usage patterns, props documentation, and converts Figma designs to production-ready vapor-ui code. Use when user asks "vapor-ui components", "vapor-ui icons", "아이콘 찾기", "vapor-ui 사용법", "vapor-ui를 사용해서 시안 구현", "convert figma", "figma to code", "implement design from figma", provides a Figma URL, or mentions specific components like "Button", "Input", "Modal".
Generate a complete Kotlin MCP server project with proper structure, dependencies, and implementation using the official io.modelcontextprotocol:kotlin-sdk library.
Create and maintain Architecture Decision Records (ADRs) optimized for agentic coding workflows. Use when you need to propose, write, update, accept/reject, deprecate, or supersede an ADR; bootstrap an adr folder and index; consult existing ADRs before implementing changes; or enforce ADR conventions. This skill uses Socratic questioning to capture intent before drafting, and validates output against an agent-readiness checklist.
Use this when users explicitly request to "generate NSFC schematic diagram/mechanism diagram" or need to convert the research mechanism, algorithm architecture, and module relationships in the proposal into "editable + embeddable" diagrams. By default, editable source files (`.drawio`) and rendered files (`.pdf`/`.svg`/`.png`) are output; when users actively mention the Nano Banana/Gemini image model, you can switch to PNG-only mode. ⚠️ Not applicable scenarios: Users only want to polish the main text (should rewrite text directly), only want to modify the format/size of existing images (should use image processing skills), and have no clear intention of requiring "schematic/mechanism diagram".
Process unstructured external input (meeting transcripts, conversation logs, pasted documents) into structured Basic Memory entities. Extracts entities, searches for existing matches, proposes new entities with approval, creates notes with observations and relations, and captures action items.
This skill should be used when the user asks about writing trading strategies, backtesting, deploying Freqtrade bots, quantitative trading, strategy optimization, or any Freqtrade-related operation. Use when user says: 'write strategy', 'create strategy', 'backtest', 'deploy Freqtrade', 'deploy bot', 'quantitative trading', 'strategy optimization', 'hyperopt', 'live trading bot', '写策略', '创建策略', '回测', '部署Freqtrade', '部署机器人', '量化交易', '量化策略', '策略优化', '超参数优化', '实盘机器人'. IMPORTANT: ALWAYS use create_strategy to generate strategy files. NEVER write Python strategy code by hand. For crypto prices/charts, use aicoin-market. For exchange trading, use aicoin-trading. For Hyperliquid, use aicoin-hyperliquid.