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identify-architecture

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Analyze ML model architecture from papers and code. Use when understanding model structure for implementation.

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How to use this skill

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Source SKILL.md: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/ai-ml/identify-architecture/SKILL.md

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Identify Architecture

Analyze and document machine learning model architectures including layers, connections, and information flow.

When to Use

  • Understanding paper model designs
  • Planning model implementation
  • Comparing architecture variations
  • Documenting neural network structure

Quick Reference

# Extract architecture from paper
# Look for: "Figure X: Architecture of [Model]"
# Check for: Table with layer specifications
# Find: Layer descriptions (Conv2D, FC, BatchNorm, etc.)

# Visualize model structure (Mojo)
# var model: SimpleNet = ...
# print(model)  # Should show layer information

Workflow

  1. Locate architecture diagram: Find visual architecture representation in paper
  2. List layers: Enumerate all layers with type and parameters
  3. Document connections: Map data flow between layers (skip connections, merges)
  4. Extract layer parameters: For each layer record size, activation, normalization
  5. Create implementation plan: Translate to Mojo struct/function definitions

Output Format

Architecture documentation:

  • Model name and source
  • Layer-by-layer breakdown
  • Layer type (Conv2D, Dense, etc.)
  • Parameters (kernel size, stride, padding, activation)
  • Input/output shapes
  • Data flow diagram (text or ASCII)
  • Special components (skip connections, attention)

References

  • See extract-hyperparameters skill for model configuration
  • See CLAUDE.md > Mojo Syntax Standards for implementation patterns
  • See /notes/review/mojo-ml-patterns.md for architecture patterns