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Code to coach

Skill MarieLynneBlock/arcanum-artifex/skills/study-support/code-to-coach

Deconstruct code into bite-sized, logical chunks from a coaching perspective. Remove abstraction, explain the "why" behind each concept, identify best practices, code smells, and cognitive load issues. Use structured frameworks to provide thorough, pedagogical analysis that teaches *how to think* about code, not just what it does.From its SKILL.md

Install
npx -y skills add MarieLynneBlock/arcanum-artifex --skill code-to-coach

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SKILL.md

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Code-to-Coach Skill

Overview

This skill transforms code analysis into a teaching and coaching dialogue. Instead of explaining what code does, it:

  1. Deconstructs into logical units (functions, classes, patterns, business logic)
  2. Removes abstraction by connecting to concrete examples and intent
  3. Explains intent — the "why" behind each decision
  4. Identifies patterns — recognises idioms, best practices, and smells
  5. Highlights cognitive load — pinpoints confusing areas and suggests clearer structures
  6. Teaches thinking patterns — helps the learner develop intuition about code structure

When to Use This Skill

Use this skill when:

  • A learner wants to understand how to think about a codebase, not just understand its current form
  • You need to identify why code is difficult to maintain or extend
  • You're reviewing code with an educational goal
  • You want to recognise anti-patterns and suggest improvements with justification
  • You need to break down complex logic into teachable chunks
  • You're preparing code for code review, documentation, or mentoring

Workflow: The Five-Step Coaching Cycle

Step 1: Orient — Scope and Context

  • Ask: What is this code's job? Who calls it? What problem does it solve?
  • Look for: Business purpose, entry/exit points, dependencies
  • Output: 1–2 sentences of clear context (remove jargon)
  • Tool: Use context-discovery.md

Step 2: Deconstruct — Break Into Chunks

  • Split the code into logical units using the deconstruction-model.md
  • Identify: Functions, loops, conditionals, state mutations, side effects, business rules
  • Name each chunk with a verb phrase (e.g., "Validate email format", "Fetch user from database")
  • Remove jargon: Translate technical terms to intent (e.g., "memoization" → "cache results to avoid recalculation")
  • Output: Annotated code or flowchart showing chunks and their relationships

Step 3: Analyse — Evaluate Quality Using the Rubric

  • Apply the analysis-rubric.md to each chunk:
    • Clarity & naming
    • Single responsibility
    • Error handling & assumptions
    • Testability & dependencies
    • Performance & resource use
    • Cognitive load (nesting depth, variable scope, mutability)
  • Identify code smells from code-smells.md
  • Note best practices from best-practices.md
  • Output: Strengths, concerns, and refactoring opportunities with rationale

Step 4: Teach — Explain the Why

  • For each chunk, answer:
    • Why was this pattern chosen?
    • What problem does it solve?
    • What trade-offs were made? (simplicity vs. performance, flexibility vs. maintainability, etc.)
    • How would a learner think about this decision?
  • Reference: Use cognitive-load.md to frame clarity issues
  • Suggest: Better names, clearer logic flow, or simpler patterns with rationale, not just opinion
  • Output: Coached explanation that builds intuition

Step 5: Advise — Next Steps

  • Prioritise refactoring opportunities using refactoring-priorities.md
  • Provide specific, actionable suggestions (with code examples if helpful)
  • Link to best-practices.md or language-specific resources
  • Output: Numbered, actionable items ranked by impact and effort

Templates & Guides

Reference Materials

Key Principles

  1. No jargon without context — Every technical term connects to intent and trade-offs
  2. Chunking first — Before analysis, divide into logical units a learner can hold in their head
  3. Why over what — Explain design decisions, not syntax
  4. Empathy — Assume the code was written with good intent; surface the constraints
  5. Actionable — Every suggestion includes rationale and effort estimate
  6. Teach thinking, not rules — Help learners develop intuition, not memorise dos and don'ts

Success Criteria

A successful coaching session:

  • ✓ Learner understands the purpose of each chunk
  • ✓ Learner can articulate why the code is structured this way
  • ✓ Learner identifies why certain areas are hard to understand
  • ✓ Learner has actionable suggestions for improvement, ranked by impact
  • ✓ Learner can apply the same thinking to unfamiliar code

Constraints & Limits

  • Language scope: Apply coaching to any language; adjust examples and idioms accordingly
  • Scale: Works best on functions or classes (up to 100–200 lines). For larger codebases, apply recursively to modules/services
  • Assumptions: Assumes the code is the real implementation, not pseudocode or incomplete logic
  • No guessing: If business context is missing, flag it and ask (don't assume intent)

Next Steps

  1. Choose a piece of code (function, class, or module)
  2. Orient yourself using context-discovery.md
  3. Deconstruct using the deconstruction-model.md
  4. Analyse against the analysis-rubric.md
  5. Teach using the teaching-script.md skeleton
  6. Advise using the coaching-review-template.md format

What ships with it: 11 files

125.3 KB alongside SKILL.md

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