AgentSkillsCN

identify-architecture

结合论文与代码，深入分析机器学习模型的架构设计，为模型的实际部署与应用做好充分准备。

SKILL.md
--- frontmatter
name: identify-architecture
description: "Analyze ML model architecture from papers and code. Use when understanding model structure for implementation."
mcp_fallback: none
category: analysis
tier: 2

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

bash
# 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