Checkpoint Preparation Guide

Prepare your module checkpoint by generating rubric reports, crafting a clear module explanation, and beginning your visual presentation.

1. Rubric Review Reports

Code Elegance Report

Ask an agent to review your code against the Code Elegance Rubric. Request that the review include:

  • Summary: 1-2 sentences capturing the overall quality and main strengths/areas for improvement
  • Findings: Assessment against each criterion (Naming Conventions, Function Design, Abstraction & Modularity, Style Consistency, Code Hygiene, Control Flow Clarity, Pythonic Idioms)
  • Scores: Points per criterion (0-4 scale)

Save as: checkpoint_X_elegance_report.md (replace X with checkpoint number)

Module Rubric Report

Ask an agent to review your module against the Module Rubric. Request the review include:

  • Summary: 1-2 sentences on module completeness and alignment with specification
  • Findings: Assessment against each criterion (Specification Clarity, Inputs/Outputs, Dependencies, Test Coverage, Documentation, Integration Readiness)
  • Scores: Points per criterion

Save as: checkpoint_X_module_report.md (replace X with checkpoint number)

2. Module Explanation (In-Person Demo)

Prepare to clearly explain your module during the in-person presentation. Be ready to discuss:

Input

  • What does your module accept? Describe the data structure, format, and constraints
  • Example: Have a concrete input example ready (e.g., "List of candidate answers: ['answer_1', 'answer_2', ...]")

Output

  • What does your module produce? Describe the data structure and format
  • Next Module Feed: Clearly articulate how this output becomes input to the next module in the pipeline (or is the final system output)

AI Concepts

  • What AI techniques are used? Be prepared to explain the core algorithms or models (e.g., "We use a Knowledge Base and forward chaining to generate new facts", "We use cosine similarity for semantic matching")
  • Why these choices? Be ready to justify why these concepts fit the problem your module solves

3. Presentation Best Practice (Optional, but STRONGLY Advised)

Start your "talk" PowerPoint now by expressing your module visually. Your slides should include:

  • Data Flow Diagram: Show how input transforms to output (boxes, arrows, data shapes)
  • Input/Output Visualization: Concrete visual example of what your module processes and produces
  • AI Concept Illustration: Visual representation of the algorithm or model (e.g., embedding space, similarity scores, decision tree branches)
  • Integration Point: Show where this module sits in the overall AI system pipeline

Starting visuals early helps clarify your thinking and ensures your explanation aligns with your implementation.

Checkpoint Readiness Checklist