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Found 1,529 Skills
Compare Nim and Python scripted agent implementations and align behavior. Use when asked to port or ensure parity between Nim and Python.
Apply the "How I Made Your Machine" coding style guide to implementation, refactoring, and code review tasks across TypeScript, Rust, and Python. Use when a request asks for this style guide, when improving maintainability and type safety, when modeling domain concepts with explicit variants/types, or when enforcing behavior-first testing.
Model Context Protocol (MCP) server development and tool management. Languages: Python, TypeScript. Capabilities: build MCP servers, integrate external APIs, discover/execute MCP tools, manage multi-server configs, design agent-centric tools. Actions: create, build, integrate, discover, execute, configure MCP servers/tools. Keywords: MCP, Model Context Protocol, MCP server, MCP tool, stdio transport, SSE transport, tool discovery, resource provider, prompt template, external API integration, Gemini CLI MCP, Claude MCP, agent tools, tool execution, server config. Use when: building MCP servers, integrating external APIs as MCP tools, discovering available MCP tools, executing MCP capabilities, configuring multi-server setups, designing tools for AI agents.
Payment gateway integration. Providers: SePay (Vietnamese: VietQR, bank transfer, cards), Polar (global SaaS: subscriptions, usage-based billing). SDKs: Node.js, PHP, Python, Go, Laravel, Next.js. Capabilities: checkout flows, subscription management, webhooks, QR code generation, benefit automation, tax compliance. Actions: integrate, implement, configure, handle payments/subscriptions/webhooks. Keywords: payment gateway, SePay, Polar, VietQR, bank transfer, subscription, usage-based billing, checkout, webhook, QR code, API key, OAuth2, product management, customer portal, tax compliance, MoR, recurring payment, invoice. Use when: integrating payment processing, implementing checkout, managing subscriptions, handling payment webhooks, generating payment QR codes, building billing systems.
Build Zerobus Ingest clients for near real-time data ingestion into Databricks Delta tables via gRPC. Use when creating producers that write directly to Unity Catalog tables without a message bus, working with the Zerobus Ingest SDK in Python/Java/Go/TypeScript/Rust, generating Protobuf schemas from UC tables, or implementing stream-based ingestion with ACK handling and retry logic.
Comprehensive pytest testing skill for Python projects. Write efficient, maintainable tests with fixtures, parametrization, markers, mocking, and assertions. Use when: (1) Writing new tests for Python code, (2) Setting up pytest in a project, (3) Creating fixtures for test dependencies, (4) Parametrizing tests for multiple inputs, (5) Mocking/patching with monkeypatch, (6) Debugging test failures, (7) Organizing test suites with markers, (8) Any Python testing task.
Test, commit, and push in one atomic workflow. Runs Go and Python tests, commits with conventional message, pushes to current branch.
Use when adding LangChain-based LLM routes or services in Python or Next.js stacks; pair with architect-stack-selector.
SOLID principles for object-oriented design — Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion. Covers motivation, violations, fixes, and multi-language examples (PHP, Java, Python, TypeScript, C++) for building maintainable, extensible software.
Integrate PICA into a LangChain/LangGraph Python application via MCP. Use when adding PICA tools to a LangChain agent, setting up PICA MCP with LangChain, or when the user mentions PICA with LangChain or LangGraph.
Docker best practices for VPS deployments in 2026. Use this skill when writing Dockerfiles, docker-compose.yml, or managing containers on a Linux VPS. Covers multi-stage builds, uv-based Python images, Xvfb/virtual display containers, volume management, security hardening, and service orchestration with Docker Compose v2. NEVER use legacy docker-compose v1 (hyphenated), old Python base images, or root containers.
Plan and execute federated analytics workflows with the Rhino Health Python SDK. Use when the user wants to run survival analysis, metrics, data harmonization, model training, or any multi-step SDK workflow. Takes high-level research goals and produces phased execution plans with runnable code. Also handles SDK questions, debugging rhino_health errors, and metric selection. Triggers on: rhino-health, rhino_health, RhinoSession, FCP, federated analytics, OMOP, FHIR, harmonization, or any of the 40+ federated metrics.