Skills

Brainstorming

IMMEDIATELY USE THIS SKILL before answering any task - internal design thinking that...

Install

npx skills add sentient-agi/EvoSkill --skill brainstorming -g -a claude-code -y
Repository
sentient-agi/EvoSkill1.3k
Category
Design
Updated
9d ago
License
Apache-2.0
Context cost
Lightabout 884 tokens
Runs scripts
No, instructions only

What it does

IMMEDIATELY USE THIS SKILL before answering any task - internal design thinking that identifies the question type, selects applicable skills, and converges on the best approach before implementation

Internal Design Thinking

Overview

Structured self-dialogue before answering any question or task. Analyze what's being asked, identify which skills apply, reason through the approach, then execute.

Core principle: Think first, execute second. Map the question to the right skill chain before acting.

The Process

Phase 1: Question Classification

Analyze the question to determine:

  • Domain: What subject area does this fall into?
  • Data type: What kind of data or input is involved?
  • Time scope: Single point, time series, comparison, or not applicable?
  • Operation type: Raw lookup, calculation, transformation, generation, analysis?
  • Output format: What form should the answer take (number, text, code, list, etc.)?
  • Key terms: If the question uses a specific term or method, explicitly state its definition/formula BEFORE proceeding

Phase 2: Skill Selection

Review available skills and determine which apply:

  1. List all skills currently available in .claude/skills/
  2. For each skill, check if it is relevant to the question's domain and operation type
  3. If multiple skills apply, determine the order they should be chained

Skill chain reasoning:

  • "This question requires [X], which maps to skill [Y]"
  • "After [Y], I need to apply [Z] for the final transformation"
  • "No existing skill covers [W], proceed with general reasoning"

Phase 3: Approach Design

For the selected skills, map out the execution path:

Read the whole SKILL.md on GitHub

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