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Personalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetition and quizes.
Comprehensive skill for building, debugging, and optimizing DZMM.AI applications. Use this skill when users request creating interactive web apps on the DZMM platform, need guidance on DZMM API usage, or require help with existing DZMM applications. Covers AI-driven chatbots, visual novels, dating sims, content generators, RPG games, content platforms, and visual effect systems. Includes state management games, message management (reroll/edit/delete), multi-opening systems, rich text rendering, modular prompt engineering, resource reuse strategies, React/Vue to DZMM migration, and responsive mobile design.
Search for and install agent skills from Hugging Face. Use this skill when users want to discover new skills, browse available skills on the Hub, or install skills to extend agent capabilities.
Context Store - Document management system for storing, querying, and retrieving documents across Claude Code sessions. Use this to maintain knowledge bases, share documents between agents. Whenever you encounter a <document id=*> in a session, use this skill to retrieve its content.
Leverage personal notes and documentation through Terraphim's role-based search. AI agents can search developer's local knowledge organized by domain (Rust, frontend, architecture) using the terraphim-agent REPL commands.
Learn about Agent Skills - how AI agents use skills, create new skills, and understand skill discovery in real-time. Use when user asks about skills, wants to create a skill, or wants to understand how Claude uses skills.
AI security co-pilot for identifying, testing, and fixing vulnerabilities in LLM-powered applications. Use when: (1) Securing LLM applications or agents, (2) Generating security test suites with promptfoo, (3) Testing for prompt injection, jailbreaking, data exfiltration, (4) Hardening system prompts, (5) Compliance mapping for OWASP LLM Top 10, NIST AI RMF, CJIS, SOC2, (6) Threat modeling AI systems, (7) Analyzing security eval results, (8) Research on LLM attack/defense techniques. Triggers: "secure my LLM", "prompt injection", "jailbreak test", "AI security", "red team", "system prompt hardening", "LLM vulnerability", "promptfoo", "OWASP LLM", "AI compliance".
This skill should be used when auditing or comparing Claude Code and Cursor IDE configurations to identify feature gaps, equivalencies, and migration opportunities. Useful when managing AI development tooling across both platforms or deciding how to structure AI workflows.
Consciousness simulation framework with Kuramoto oscillators, APL operators, and K-formation dynamics. Use for physics simulations, phase transitions, coherence analysis, and cloud training via GitHub Actions. Requires numpy and requests packages.
The OpenAI REST API. Please see https://platform.openai.com/docs/api-reference for more details.
Fine-tunes TimeGPT on custom datasets to improve forecasting accuracy. Use when TimeGPT's zero-shot performance is insufficient or domain-specific accuracy is needed. Trigger with "finetune TimeGPT", "train TimeGPT", "adapt TimeGPT".
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predictions, propose mechanisms, and design experiments to test them. Follows scientific method framework. For open-ended ideation use scientific-brainstorming; for automated LLM-driven hypothesis testing on datasets use hypogenic.
Framework for building AI agents that work effectively across multiple context windows on complex, long-running tasks. Use when building agents for multi-hour/multi-day projects, implementing persistent coding workflows, creating systems that need state management across sessions, or when an agent needs to make incremental progress on large codebases. Provides initializer and coding agent patterns, progress tracking, feature management, and session handoff strategies.
NVIDIA NIM inference microservices for deploying AI models with OpenAI-compatible APIs, self-hosted or cloud
Build AI agents with Google ADK Python (Agent Development Kit). Use for multi-agent systems, workflow agents (sequential/parallel/loop), Vertex AI deployment, tool integration, human-in-the-loop.
Evaluate Claude Code skills against best practices including size, structure, examples, and prompt engineering quality. Provides comprehensive analysis with actionable suggestions.
