explaining-codebases skill

Explaining Codebases

Overview

This skill explains code as it actually exists - a repository, a service, or a set of source files. The output is the same distill-style, single self-contained interactive explainer that creating-explainers produces. What differs is the intake (navigating real code instead of reading a paper) and the figure types (architecture diagrams, data-flow, execution traces, annotated code walkthroughs). It handles both onboarding overviews of a whole codebase and deep-dives on one mechanism.

Required Background

REQUIRED: Use creating-explainers for everything about the output - the HTML template, voice and style, base figure archetypes, color palettes, the outline/scaffold/prose/polish workflow, and the quality checklist. This skill only adds what is specific to code. Do not duplicate that material here.

When to Use

Use when the subject is code:

• Architecture / onboarding overview - how a project is structured: its modules, how data flows between them, the key abstractions, how the pieces fit. For a new contributor who needs the map.
• Single-mechanism deep-dive - how one algorithm, feature, or subsystem works, traced through the real implementation.

The skill picks the angle from the request and confirms it with the user during intake (overview and deep-dive want different figures and different depth).

When NOT to use: a paper, a topic, or any non-code source. Use creating-explainers instead.

Code Intake

See references/code-intake.md. In short: pick the angle, navigate the repository to find entry points and module structure, identify the spine concept (the one path or idea the article tracks), map the architecture, and pull real code snippets anchored to path:line. Quote actual code; never paraphrase code as if quoting it.

Code-Specific Figures

See references/code-figure-archetypes.md for the patterns:

• Architecture / module diagram - modules as boxes, dependencies as arrows
• Data-flow / sequence diagram - an item (request, message, token) moving through stages
• Execution-trace stepper - step through an algorithm with state and the current line highlighted
• Annotated code walkthrough - a code block whose lines reveal annotations as you step or hover

The mechanics (DPR-aware initCanvas, the IIFE pattern, animation loops) come from the base figure-archetypes.md in creating-explainers. The code-figure reference only covers how to apply them to code.

The Fact-Check Gate for Code

REQUIRED before delivery: run fact-checking-explainers. For a codebase explainer the source of truth is the code itself. Every claim about what the code does, and every quoted snippet, is checked against the actual implementation at a specific path and line. Code drifts; a snippet that was accurate yesterday may be wrong today. The interactive explainer is not done until it passes.

Workflow

Same staged workflow as creating-explainers, with code intake in place of the text intakes:

1. Code intake           -> navigate, pick angle, find the spine, map architecture, pull real snippets
2. Outline               -> propose sections + figure list, get user approval
3. Scaffold              -> copy the article template, fill metadata
4. Prose pass            -> write all sections with figure placeholders
5. Figures pass          -> implement each interactive figure
6. Post-draft fact-check -> verify every claim and snippet against the real code (REQUIRED, blocking)
7. Polish                -> run the creating-explainers Quality Checklist to completion

Pause for user approval after the outline. Everything about scaffolding, prose, figures, polish, and the delivery checklist follows creating-explainers.

Common Mistakes

Mistake	Fix
Explaining code that does not exist, or that you imagined	Open the files. Every claim traces to real code at a real path.
Snippets drift from the real source	Quote exactly, with path:line. Never tidy code into something the repo does not contain.
Architecture diagram does not match the real module structure	Build the diagram from the actual imports and call sites, not a guess.
Scope too broad (a whole framework in one article)	Pick one subsystem or one mechanism. Breadth dilutes; depth teaches.
Pasting a huge file as a "figure"	Figures illustrate a point the prose just set up. Trim to the lines that matter.