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Found 803 Skills
Complete reference for Runway's public API: models, endpoints, costs, limits, and types
Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
Implement API versioning strategies including URL versioning, header versioning, backward compatibility, deprecation strategies, and migration guides. Use when dealing with API versions, deprecating endpoints, or managing breaking changes.
Advanced WordPress development with REST API endpoints, WP-CLI commands, performance optimization, and caching strategies for scalable applications.
Test for user enumeration vulnerabilities through various authentication endpoints.
Code style, architecture patterns, and development guide for the Droplinked e-commerce backend. NestJS + Prisma (MongoDB) with strict layered architecture: Controller to Service Facade to UseCase to Repository. Use this skill when: (1) Creating new features, modules, or endpoints in the Droplinked backend (2) Refactoring existing code to follow project patterns (3) Writing tests for use cases and services (4) Reviewing code for architectural compliance (5) Understanding the data model (shops, products, orders, carts, merchants, customers) (6) Implementing cross-module communication (7) Adding event-driven side effects (8) Working with Prisma and MongoDB in this codebase Triggers: droplinked, nest module, usecase, service facade, repository pattern, cart, order, shop, product, merchant
CLI tools execution specification (gemini/claude/codex/qwen/opencode) with unified prompt template, mode options, and auto-invoke triggers for code analysis and implementation tasks. Supports configurable CLI endpoints for analysis, write, and review modes.
Create and refine HEARTBEAT.md files for murmur — a CLI daemon that runs scheduled Claude prompts on a cron or interval schedule. Use this skill when the user wants to set up a recurring automated action (e.g., "monitor my GitHub issues", "check Hacker News for AI articles", "watch my endpoints", "send me a daily digest"). Guides the user through an interview, drafts the heartbeat prompt, tests it, and registers it with murmur's scheduler. Triggers: heartbeat, murmur, recurring task, scheduled action, cron, monitor, watch, automate, periodic check, scheduled prompt.
Generate images and videos using x402-protected AI models at StableStudio. USE FOR: - Generating images from text prompts - Generating videos from text or images - Editing images with AI - Creating visual content TRIGGERS: - "generate image", "create image", "make a picture" - "generate video", "create video", "make a video" - "edit image", "modify image" - "stablestudio", "nano-banana", "sora", "veo" ALWAYS use `npx agentcash fetch` or `npx agentcash fetch-auth` for stablestudio.dev endpoints.
Guides feature development in Fusion Framework React apps, including app-scoped framework research needed to choose the right hooks, modules, packages, and integration patterns before implementation. USE FOR: building new features, adding components or pages, creating hooks and services, wiring up API endpoints, extending Fusion module configuration, and answering app implementation questions about which Fusion Framework surface to use. DO NOT USE FOR: issue authoring, skill authoring, CI/CD configuration, backend service changes, or general Fusion documentation that is not tied to app implementation.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.