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Found 286 Skills
Use when creating or developing anything, before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validation
This skill should be used when the user asks to "use the oracle" or "ask the oracle" for deep research, analysis, or architectural questions. The oracle excels at multi-source research combining codebase exploration and web searches, then synthesizing findings into actionable answers. Use for complex questions requiring investigation across multiple sources, architectural analysis, refactoring plans, debugging mysteries, and code reviews.
Illustre automatiquement le journal d'une aventure BFRPG en générant des images pour les moments clés (combats, explorations, découvertes). Utilise la génération parallèle pour une performance optimale.
Invoke IMMEDIATELY via python script when user requests refactoring analysis, technical debt review, or code quality improvement. Do NOT explore first - the script orchestrates exploration.
Log exploration and analysis using Quickwit search engine. Incident investigation, error pattern analysis, and observability workflows. Three index discovery modes for different performance and convenience trade-offs.
Deep web research with parallel investigators, multi-wave exploration, and structured synthesis. Spawns multiple web-researcher agents to explore different facets of a topic simultaneously, launches additional waves when gaps are identified, then synthesizes findings. Use when asked to research, investigate, compare options, find best practices, or gather comprehensive information from the web.\n\nThoroughness: quick for factual lookups | medium for focused topics | thorough for comparisons/evaluations (waves continue while critical gaps remain) | very-thorough for comprehensive research (waves continue until satisficed). Auto-selects if not specified.
Build explorative, interactive learning experiences as Next.js apps using the Geist design system. Use when creating tutorials, explorable explanations, interactive lessons, code sandboxes, quizzes, or any educational UI. Covers the Learning Loop pedagogy, 23+ learning component patterns, progress tracking, spaced repetition, and Bret-Victor-style interactive exploration — all with Geist's dark-first minimal aesthetic.
Use when "training LLM", "finetuning", "RLHF", "distributed training", "DeepSpeed", "Accelerate", "PyTorch Lightning", "Ray Train", "TRL", "Unsloth", "LoRA training", "flash attention", "gradient checkpointing"
Interactive web apps for data science: Streamlit, Panel, and Gradio. Use for prototyping ML models, creating data exploration dashboards, and sharing insights with non-technical stakeholders.
Multi-Model Collaboration — Invoke gemini-agent and codex-agent for auxiliary analysis **Trigger Scenarios** (Proactive Use): - In-depth code analysis: algorithm understanding, performance bottleneck identification, architecture sorting - Large-scale exploration: 5+ files, module dependency tracking, call chain tracing - Complex reasoning: solution evaluation, logic verification, concurrent security analysis - Multi-perspective decision-making: requiring analysis from different angles before comprehensive judgment **Non-Trigger Scenarios**: - Simple modifications (clear changes in 1-2 files) - File searching (use Explore or Glob/Grep) - Read/write operations on known paths **Core Principle**: You are the decision-maker and executor, while external models are consultants.
Use when solution space exploration is complete and you're ready to create an implementation plan. Enforces "simple over easy" - the fundamentally right solution, not the path of least resistance. Triggers after /design-solution, when a solution has been chosen, or when asked to "make a plan" or "create a plan".
Learn about Moralis and Web3 development. Invoked without a question, gives a friendly platform walkthrough — what's available, what data you can fetch, and how everything fits together. Invoked with a question, answers it directly. Use for "what is Moralis", "can Moralis do X", "what chains are supported", "how do I get started", "which API should I use", pricing, feature comparisons, or any exploratory questions. Routes to the correct technical skill (@moralis-data-api or @moralis-streams-api) after answering.