Deepstack skill

The video demonstrates the "Deep Stack" skill, a tool designed to create highly specific prompts for deep research, particularly when facing technical challenges or planning new features in software development.

Here's a breakdown:

• Problem: The presenter wants to implement split-pane terminals in the Solo desktop application (a REST-based Tauri app). He is unsure how to handle input/output routing, PTY, and multiple xterm instances.
• Deep Stack Functionality: Deep Stack analyzes the project's technology stack (REST, Tauri, Portable-PTY, xterm, SQLite, etc.) and generates a tailored prompt for a research agent. It identifies specific versions of libraries used. It's crucial for providing accurate guardrails for the research process.
• Benefits of Deep Stack: The generated prompt provides context to the research agent, including the current architecture (PTY routing, input handling, etc.). This prevents irrelevant suggestions that would require major overhauls.
• Example Prompt Breakdown: The prompt includes:
  • The project's technology stack
  • A description of the current architecture.
  • Specific areas for research: XTerm multi-instance, PTY handling, input routing, split-pane layouts, state management, performance considerations (WebGL limits on macOS).
  • Suggestions to look for existing implementations like VS Code.
  • Areas of focus, anti-patterns to avoid, and resources to consider.
• Research Process: The presenter copies the Deep Stack generated prompt and pastes it into a research tool like Claude AI or Gemini (with deep research enabled). These tools then conduct web searches and generate a detailed research report (usually taking around 40 minutes).
• Using the Research Report: The research report is downloaded and saved within the project's directory (typically in a git-ignored "Agents" folder and a "Reference" folder). The presenter then uses a tool like Claude on the CLI in plan mode to analyze the report and develop an implementation plan. They may also consult other code generation tools to ensure a thorough approach.
• Key Takeaway: Deep Stack helps create high-quality, stack-specific prompts, enabling research agents to provide relevant and actionable insights, saving time and avoiding irrelevant research.