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Found 1,137 Skills
End-to-end feature owner with expertise across the entire stack. Delivers complete solutions from database to UI with focus on seamless integration and optimal user experience.
Interactive project planning for PRD, architecture, and epic/story generation. Use for new projects, planning features, creating PRDs, designing architecture, breaking down work into epics and stories.
Multi-model consensus council for validation, research, and brainstorming. Spawns parallel judges with configurable perspectives and optional explorer sub-agents using runtime-native backends (Codex sub-agents or Claude teams). Modes: validate, brainstorm, research. Triggers: council, validate, brainstorm, critique, research, analyze, multi-model, consensus.
Analyze footnotes and accounting policies from SEC filings using Octagon MCP. Use when researching revenue recognition policies, critical estimates, lease obligations, pension assumptions, stock compensation, contingencies, and new accounting pronouncements.
Deep Reading Collaborative System: A system leveraging multi-layered AI Agents to help transform articles from "read" to "understood" to "mastered", and convert knowledge into actionable plans. Use this system when you need to deeply understand complex articles/papers, systematically organize reading notes, think critically about content, discover hidden logical issues and assumptions, or turn knowledge into action plans. Trigger keywords: deep reading, critical thinking, reading notes, article analysis, Socratic questioning, action plan
Browser automation for AI agents. Use when the user needs to navigate websites, read page content, fill forms, click elements, take screenshots, or manage browser tabs.
General Architecture Governance Specification, providing layering constraints, impact analysis, interface contracts, and dependency injection baselines. Suitable for architecture review, refactoring, and new module design of any multi-layer system.
[PREREQUISITE] Install and configure Godot MCP server for programmatic scene manipulation via Model Context Protocol. Use when user explicitly requests MCP-based scene building or automation. NOT for manual Godot workflows. Keywords MCP, Model Context Protocol, scene automation, npx, claude_desktop_config.
Project setup. Explore the codebase, ask about strategy and aims, write persistent context to AGENTS.md. Run when starting or when aims shift.
Expert in building comprehensive AI systems, integrating LLMs, RAG architectures, and autonomous agents into production applications. Use when building AI-powered features, implementing LLM integrations, designing RAG pipelines, or deploying AI systems.
Initialize projects with agentic coding structure. Use when setting up a new project, adding AI agent support to existing project, or when user says "init", "initialize", "setup project", or "scaffold". Creates AGENTS folder, documentation templates, and _NOTES scratch space.
Facilitate workshop sessions in a multi-turn, one-step flow with numbered recommendations at decision points and quick-select options for regular questions.