Agent skill

deep-reason

Esta skill debe usarse cuando el usuario pide "pensemos esto a fondo", "analicemos paso a paso", "evaluemos opciones", "razonemos sobre esto", "pensemos detenidamente", "meditemos", "qué me sugieres", "qué me recomiendas", "esto es complejo", "esto es complicado", "problema grande", o ante problemas que requieren análisis profundo, afectan múltiples componentes del sistema, tienen implicaciones arquitectónicas importantes, o representan decisiones de diseño con impacto significativo. IMPORTANTE: Invocar esta skill en lugar de usar seq-think MCP directamente - la skill proporciona workflow estructurado con generación de documentos de análisis.

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npx add-skill https://github.com/DieGopherLT/dotclaudefiles/tree/main/plugins/dotclaudefiles/skills/deep-reason

SKILL.md

To engage in deep, structured reasoning for complex problems, apply the sequential-thinking approach with these guidelines:

Thought Process Guidelines

During the sequential thinking process:

1. Initial Thoughts: Problem Space Definition

  • Reduce scope if the problem is too broad or unfocused
  • Create the problem space: Define the problem itself WITHOUT any influence from solutions or tools
    • See the problem as it truly is, not through the lens of potential solutions
    • Identify core constraints, requirements, and success criteria
    • Separate facts from assumptions

2. Solution Generation

  • Generate multiple options or solutions to the stated problem
  • Consider diverse approaches, not just the most obvious ones
  • Think creatively about different paths to the goal

3. Information Gathering

  • Gather information as needed throughout the thought process
  • Use tools (Read, Grep, Glob, WebFetch, MCPs, specialized agents, etc.) to understand:
    • The problem better
    • Existing code/patterns
    • Any proposed solutions
    • Technical constraints or documentation

4. Option Evaluation

  • Evaluate each option thoroughly, considering:
    • Pros: Benefits, strengths, advantages
    • Cons: Drawbacks, risks, limitations
    • Trade-offs between options
    • Implementation complexity
    • Long-term maintainability

5. Use Branches for Multiple Options

  • When thinking through multiple distinct options or solutions, use the branch feature of the MCP:
    • branchFromThought: Specify which thought number is the branching point
    • branchId: Give each branch a descriptive identifier (e.g., "option-redis", "option-inmemory")
  • This allows parallel exploration of different approaches

After Completing the Thought Chain

After completing the sequential thinking process and reaching a conclusion:

  1. Present findings to the user concisely

  2. Ask if they want a summary document using the AskUserQuestion tool:

    • Question: "Would you like me to generate a summary document of the knowledge and analysis generated during this reasoning process?"
    • Options:
      • "Yes, generate summary" (description: "I'll create a detailed document with the complete analysis, evaluated options, and conclusions")
      • "No, continue without summary" (description: "We'll proceed without generating the summary document")
  3. When user chooses "Yes, generate summary":

    • Use the template from summary-template.md in this skill directory
    • Fill template sections with information from the thought chain
    • Save to an appropriate location (docs/, project root, or user-specified)
    • Use descriptive filename with timestamp (e.g., sequential-reasoning-summary-2026-01-14.md)

Important Notes

  • Be thorough but efficient: Don't add thoughts just to increase the count
  • Revise when needed: Use isRevision: true and revisesThought if earlier thinking was flawed
  • Branch when exploring: Use branches to explore multiple paths simultaneously
  • Gather context: Don't hesitate to use tools mid-thought-chain to gather necessary information
  • Express uncertainty: If unsure, express it and explore alternatives
  • Stop when done: Set nextThoughtNeeded: false only when truly satisfied with the solution

Resources

Summary Template

  • summary-template.md - Comprehensive template for knowledge synthesis documents including:
    • Problem space definition
    • Options generation and evolution tracking
    • Comparative analysis (tables for 2 options, lists for 3+)
    • Conclusions with pros/cons
    • Recommendations and next steps

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