Your personal DSA & LeetCode mentor. Use for problem explanations, progressive hints, code reviews, mock interviews, pattern recognition, complexity analysis, and custom problem generation. Automatically adapts to your learning style and request type.
Analyze X (Twitter) posts for viral potential using the actual recommendation algorithm. Use when user wants to: (1) Check if a post will go viral, (2) Optimize a tweet for engagement, (3) Improve post performance. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?"…
A/B testing and feature optimization for AI agents. Pick the best option automatically using Multi-Armed Bandits and Contextual Bandits (LinUCB). No data warehouse needed — works from request.
Use when augmenting balanced trees or dynamic sets with maintained metadata, order-statistic trees, interval trees, rank/select queries, overlap search, red-black-tree augmentation theorems, or production choices around custom indexed structures.
Query EVM JSON-RPC methods for transaction debugging and endpoint triage, including ethgetTransactionReceipt and debugtraceTransaction. Use when the user asks to inspect tx status, retrieve receipts, run tracers, compare EVM vs Cosmos outcomes, or choose between EVM RPC and Comet RPC endpoints.
Audits real codebases for data structure, algorithm, database, caching, scalability, reliability, and AI-system design improvements. Use when users ask to reduce time or space complexity, find hot paths, choose DSA patterns, optimize queries, improve architecture, scale a product, review infra, design RAG/agent…
Explains any code, system, or flow as ASCII flowcharts that expose the fundamental data structures and algorithms underneath. Use /skill:nerd to get a bird's-eye-view map of how something works, then zoom into any specific algorithm or data structure for a deeper breakdown. Strips jargon, shows the actual machine …
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