music-theory-visual-design
Visual design and UI styling guidelines for the Harmonic Orbit music theory application, covering typography, color systems, spacing, animations, and accessibility standards.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
426 skills found
Visual design and UI styling guidelines for the Harmonic Orbit music theory application, covering typography, color systems, spacing, animations, and accessibility standards.
Search and execute dynamic external tools via the QVeris API for real-time data retrieval, stock market analysis, and web-based tasks.
A standardized template for creating and documenting modular Agent Skills to ensure consistent, efficient context engineering across AI agent systems.
Comprehensive mobile testing for iOS and Android, covering gestures, sensors, permissions, device fragmentation, and performance across 1000+ real and virtual devices.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.
Development guide for Arma Reforger EnforceScript, covering component architecture, network replication, persistence, and memory management.
Neural web search and code context retrieval via Exa AI. Ideal for documentation, technical research, code examples, and company intelligence.
A framework for software teams and AI agents to prevent feature creep, enforce scope discipline, and ship focused MVPs by applying strict validation, backlog hygiene, and clear decision-making processes.
Convert various documents, media, and web content into Markdown using markitdown, ideal for LLM processing and text analysis.
Audit and optimize your AI prompts with Token Surgeon. Detect 10 common waste patterns, calculate efficiency, and reduce token usage for better prompt performance.
Systematic debugging workflow for MCP servers and Microsoft Copilot Studio integrations, featuring common fix patterns and validation scripts.
Epistemic safety analysis for JSON data in prompts to prevent LLM hallucinations and reasoning errors when handling incomplete or large-scale datasets.