deep▌

Status: Production Ready Last Updated: 2026-02-03 Dependencies: Chrome MCP tools (optional), debugger agent, code-reviewer agent

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

A powerful, self-contained deep research skill that produces thorough, cited reports from multiple web sources. No paid APIs required — uses DuckDuckGo search.

Full 5-layer analysis of a specific function. Use when debugging or deeply understanding code.

Run autonomous research tasks that plan, search, read, and synthesize information into comprehensive reports.

Systematic literature research: disambiguate, search with collision-aware queries, grade evidence, produce structured reports.

I help you conduct comprehensive, multi-faceted research on any topic. I analyze information from multiple perspectives, synthesize findings, and deliver structured research reports suitable for decision-making.

Expert guidance for deep learning, transformers, diffusion models, and LLM development with PyTorch. \n \n Covers PyTorch model architectures, transformers, diffusion models, and LLM fine-tuning with libraries including Transformers, Diffusers, and Gradio \n Emphasizes GPU optimization, mixed precision training, distributed training, and gradient accumulation for efficient workflows \n Includes best practices for data loading, train/validation splits, early stopping, learning rate scheduling, an

This skill provides a systematic methodology for conducting thorough web research. Load this skill BEFORE starting any content generation task to ensure you gather sufficient information from multiple angles, depths, and sources.

Answers: "Who is this wallet and what have they been doing?"