Abstraction Ladder Framework

SkillAI & models

Builds structured abstraction ladders that translate high-level principles into concrete, actionable examples across 3-5 levels. Bridges communication gaps, reveals hidden assumptions, and tests whether abstract ideas work in practice. Use when explaining concepts at different expertise levels, moving between abstract principles and concrete implementation, identifying edge cases by testing ideas against scenarios, designing layered documentation, decomposing complex problems into actionable steps, or bridging strategy-execution gaps.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Abstraction Ladder Framework skill

What this skill tells your AI

The instructions your AI receives, as published by lyndonkl/claude in skills/abstraction-concrete-examples/SKILL.md and read by ahel’s review.

Table of Contents

  • Workflow
    • 1. Gather Requirements
    • 2. Choose Approach
    • 3. Build the Ladder
    • 4. Validate Quality
    • 5. Deliver and Explain
  • Common Patterns
  • Guardrails
  • Quick Reference

The ladder uses 3-5 levels connecting universal principles to concrete details. Example:

  • L1: "Software should be maintainable"
  • L2: "Use modular architecture"
  • L3: "Apply dependency injection"
  • L4: "UserService injects IUserRepository"
  • L5: constructor(private repo: IUserRepository) {}

Workflow

Copy this checklist and track your progress:

Abstraction Ladder Progress:
- [ ] Step 1: Gather requirements
- [ ] Step 2: Choose approach
- [ ] Step 3: Build the ladder
- [ ] Step 4: Validate quality
- [ ] Step 5: Deliver and explain

Step 1: Gather requirements

Ask the user to clarify topic, purpose, audience, scope (suggest 4 levels), and starting point (top-down, bottom-up, or middle-out). This ensures the ladder serves the user's actual need.

Step 2: Choose approach

For straightforward cases with clear topics → Use resources/template.md. For complex cases with multiple parallel ladders or unusual constraints → Study resources/methodology.md. To see examples → Show user resources/examples/ (api-design.md, hiring-process.md).

Step 3: Build the ladder

Create abstraction-concrete-examples.md with topic, 3-5 distinct abstraction levels, connections between levels, and 2-3 edge cases. Ensure top level is universal, bottom level has measurable specifics, and transitions are logical. Direction options: top-down (principle → examples), bottom-up (observations → principles), or middle-out (familiar → both directions).

Step 4: Validate quality

Self-assess using resources/evaluators/rubric_abstraction_concrete_examples.json. Check: each level is distinct, transitions are clear, top level is universal, bottom level is specific, edge cases reveal insights, assumptions are stated, no topic drift, serves stated purpose. Minimum standard: Average score ≥ 3.5. If any criterion < 3, revise before delivering.

Step 5: Deliver and explain

Present the completed abstraction-concrete-examples.md file. Highlight key insights revealed by the ladder, note interesting edge cases or tensions discovered, and suggest applications based on their original purpose.

Common Patterns

For communication across levels:

  • Share L1-L2 with executives (strategy/principles)
  • Share L2-L3 with managers (approaches/methods)
  • Share L3-L5 with implementers (details/specifics)

For validation:

  • Check if L5 reality matches L1 principles
  • Identify gaps between adjacent levels
  • Find where principles break down

For design:

  • Use L1-L2 to guide decisions
  • Use L3-L4 to specify requirements
  • Use L5 for actual implementation

Guardrails

Do:

  • State assumptions explicitly at each level
  • Test edge cases that challenge the principles
  • Make concrete levels truly concrete (numbers, measurements, specifics)
  • Make abstract levels broadly applicable (not domain-locked)
  • Ensure each level is understandable given the previous level

Don't:

  • Use vague language ("good", "better", "appropriate") without defining terms
  • Make huge conceptual jumps between levels
  • Let different levels drift to different topics
  • Skip the validation step (the rubric check ensures quality)
  • Front-load expertise - explain clearly for the target audience

Quick Reference

  • Template for standard cases: resources/template.md
  • Methodology for complex cases: resources/methodology.md
  • Examples to study: resources/examples/api-design.md, resources/examples/hiring-process.md
  • Quality rubric: resources/evaluators/rubric_abstraction_concrete_examples.json

Signals

GitHub stars
158
Forks
23
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
abstraction-concrete-examples
Source
github.com/lyndonkl/claude