Develop with
Superpowers

This skill should be used when writing or improving system prompts for AI agents, providing expert guidance based on Anthropic's context engineering principles.

NautilusTrader algorithmic trading platform. Use for building trading strategies, backtesting, live trading, data handling, and quantitative finance applications.

Build conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Expert guidance for distributed training with DeepSpeed - ZeRO optimization stages, pipeline parallelism, FP16/BF16/FP8, 1-bit Adam, sparse attention

Build MCP servers in Python with FastMCP framework to expose tools, resources, and prompts to LLMs. Supports storage backends (memory/disk/Redis), middleware, OAuth Proxy, OpenAPI integration, and FastMCP Cloud deployment. Use when: creating MCP servers, defining tools or resources, implementing OAuth authentication, configuring storage backends for tokens/cache, adding middleware for logging/rate limiting, deploying to FastMCP Cloud, or troubleshooting module-level server, storage, lifespan, middleware order, circular imports, or OAuth errors. Keywords: FastMCP, MCP server Python, Model Context Protocol Python, fastmcp framework, mcp tools, mcp resources, mcp prompts, fastmcp storage, fastmcp memory storage, fastmcp disk storage, fastmcp redis, fastmcp dynamodb, fastmcp lifespan, fastmcp middleware, fastmcp oauth proxy, server composition mcp, fastmcp import, fastmcp mount, fastmcp cloud, fastmcp deployment, mcp authentication, fastmcp icons, openapi mcp, claude mcp server, fastmcp testing, storage misconfiguration, lifespan issues, middleware order, circular imports, module-level server, async await mcp

Build type-safe validated forms in React using React Hook Form and Zod schema validation. Single schema works on both client and server for DRY validation with full TypeScript type inference via z.infer. Use when: building forms with validation, integrating shadcn/ui Form components, implementing multi-step wizards, handling dynamic field arrays with useFieldArray, or fixing uncontrolled to controlled warnings, resolver errors, async validation issues.

Provides expertise on how to plan for work in this repo

Provide a systematic debugging checklist. Use when a junior developer is stuck and needs a structured approach.

Create a staged refactor plan for a module. Use when a mid-level developer needs a safe refactor path.

World-class prompt powerhouse that generates production-ready mega-prompts for any role, industry, and task through intelligent 7-question flow, 69 comprehensive presets across 15 professional domains (technical, business, creative, legal, finance, HR, design, customer, executive, manufacturing, R&D, regulatory, specialized-technical, research, creative-media), multiple output formats (XML/Claude/ChatGPT/Gemini), quality validation gates, and contextual best practices from OpenAI/Anthropic/Google. Supports both core and advanced modes with testing scenarios and prompt variations.

Analyzes technical systems and problems through engineering lens using first principles, systems thinking, design methodologies, and optimization frameworks. Provides insights on feasibility, performance, reliability, scalability, and trade-offs. Use when: System design, technical feasibility, optimization, failure analysis, performance issues. Evaluates: Requirements, constraints, trade-offs, efficiency, robustness, maintainability.

Analyzes events through indigenous knowledge systems using relational thinking, seven generations principle, reciprocity, holistic integration, and traditional ecological knowledge frameworks. Provides insights on interconnectedness, long-term sustainability, collective wisdom, and decolonial perspectives. Use when: Environmental decisions, resource stewardship, community governance, decolonization, intergenerational planning. Evaluates: Relationships, sustainability, collective impact, indigenous rights, traditional knowledge integration.

Analyzes disease patterns and health events through epidemiological lens using surveillance systems, outbreak investigation methods, and disease modeling frameworks. Provides insights on disease spread, risk factors, prevention strategies, and public health interventions. Use when: Disease outbreaks, health policy evaluation, risk assessment, intervention planning. Evaluates: Transmission dynamics, risk factors, causality, population health impact, intervention effectiveness.

Generates agentic outside-in tests using gadugi-agentic-test framework for CLI, TUI, Web, and Electron apps. Use when you need behavior-driven tests that verify external interfaces without internal implementation knowledge. Creates YAML test scenarios that AI agents execute, observe, and validate against expected outcomes. Supports progressive complexity from simple smoke tests to advanced multi-step workflows.

Interactive planning skill for Amp. Generates specs, implementation plans, and loop infrastructure through clarifying questions.

Analyze mistakes with conversation length as potential cause (CAT-specific)

Meta-skill that indexes, optimizes, and auto-generates Claude skills with GitOps automation, OCA GitHub bot integration, and Odoo developer tools. Use for skill creation, CI/CD workflows, OCA module management, and advanced Odoo development.

Performs systematic code review with universal best practices and repo-specific standards. Auto-activates after significant code changes. Use when reviewing code, auditing files, checking PRs, examining staged changes, or when asked to "review", "check", "audit", or "examine" code. Enforces design principles (SOLID, DRY, KISS), security (OWASP), performance, concurrency safety, cross-platform compatibility, and codebase patterns.

Zero Trust architecture principles including ZTNA, micro-segmentation, identity-first security, continuous verification, and BeyondCorp patterns. Use when designing network security, implementing identity-based access, or building cloud-native applications with zero trust principles.