Explain Codebase

Generate a FOR_[NAME].md document that explains a codebase, project, or domain in an engaging, memorable way.

What Makes This Different

This isn't documentation. Documentation tells you what exists. This tells you:

• Why decisions were made
• How the pieces connect
• What you'll wish you knew sooner
• Where the dragons live (and how to avoid them)

The output should read like a senior engineer explaining the project over coffee, not like a README.

Input Detection

Check $ARGUMENTS:

Phase 1: Gather Context

1.1 Ask Initial Questions

Use AskUserQuestion to understand scope:

What should I focus on?

Options:
1. Full codebase overview (architecture, patterns, lessons)
2. Specific subsystem or feature
3. Recent changes and their rationale
4. Onboarding guide for new contributors

1.2 Explore the Codebase

Use the Explore agent to understand structure:

Task({
  subagent_type: "Explore",
  description: "Map codebase architecture",
  prompt: `
    Explore this codebase and identify:
    1. Main entry points
    2. Core abstractions and patterns
    3. Directory structure philosophy
    4. Key configuration files
    5. Test patterns
    6. External dependencies and why they're used

    Return a structured summary, not raw file listings.
  `
})

1.3 Find the Interesting Bits

Look for:

• CLAUDE.md / README.md - Existing documentation to build on
• CHANGELOG.md - History of decisions and pivots
• package.json / Cargo.toml / etc - Dependencies tell stories
• Test files - Show how things are meant to be used
• Config files - Reveal hidden assumptions
• Comments with "TODO", "HACK", "FIXME" - Where the bodies are buried

Grep({ pattern: "TODO|HACK|FIXME|XXX|NOTE:", output_mode: "content" })

Phase 2: Identify the Story

Every codebase has a narrative. Find it.

2.1 The Problem Statement

What pain does this code solve? Not the feature list—the actual human frustration it addresses.

Bad: "This is a task management CLI" Good: "This exists because every task app assumes you'll check it daily, but ADHD brains don't work that way"

2.2 The Key Decisions

What architectural choices were made and why? Look for:

• Why this language/framework?
• Why this folder structure?
• Why these abstractions?
• What was tried and abandoned?

2.3 The Lessons Learned

What would someone wish they knew before diving in? This includes:

• Non-obvious gotchas
• Performance cliffs
• Security considerations
• "It looks simple but actually..."

Phase 3: Structure the Document

Use this template structure, adapting sections as needed:

# [Project Name]: The Story Behind the Code

*[One-line hook that makes someone want to read more]*

---

## The Problem We're Actually Solving

[Start with the human problem, not the technical solution]

---

## The Architecture: [Memorable Analogy]

[Use an analogy that makes the structure intuitive]
[Include ASCII diagrams where helpful]

### Why This Separation Matters

[Explain the reasoning, not just the structure]

---

## The Technical Stack (And Why Each Piece)

### [Technology 1]

[What it is, why we chose it, what we'd lose without it]

### [Technology 2]

[Same pattern - every tool earns its place]

---

## [Core Feature/System Deep Dive]

[Pick the most interesting/complex part and explain it thoroughly]

### The Problem It Solves

[Specific pain point]

### The Solution

[How it works, with code examples where helpful]

### Why This Approach

[Alternative approaches considered and rejected]

---

## Bugs We Hit (And How We Fixed Them)

### Bug #1: [Descriptive Name]

**Symptom:** [What you saw]
**Root Cause:** [What was actually wrong]
**Fix:** [What we did]
**Lesson:** [What to remember]

[Repeat for significant bugs]

---

## Best Practices Embedded in This Codebase

### 1. [Practice Name]

[Explain the practice and show an example from the code]

[Repeat for 3-5 key practices]

---

## How Good Engineers Think

[Meta-lessons about engineering mindset learned from this project]

---

## What's Next

[Future directions this architecture enables]

---

## Final Thoughts

[Wrap up with the core insight or philosophy]

---

*— [Sign-off that fits the project's personality]*

Phase 4: Write with Engagement

Use These Techniques

1. Analogies Over Abstractions

Instead of:

"The event system uses a pub-sub pattern with topic-based routing"

Write:

"Think of it like a newspaper. Publishers write articles, subscribers pick which sections they care about. The event bus is the printing press—it doesn't care what's in the message, just where it needs to go."

2. Show the Evolution

Instead of:

"We use worker threads for CPU-intensive tasks"

Write:

"Version 1 was single-threaded. Then we hit a wall processing 10,000 records—users stared at a frozen screen for 30 seconds. Worker threads turned that into a 3-second background job. The code is uglier, but the UX is worth it."

3. Honest About Trade-offs

Instead of:

"The system is highly scalable"

Write:

"It scales horizontally, but there's a catch: every new instance needs 2GB RAM for the in-memory cache. At 10 instances, you're paying for 20GB of RAM that's 80% duplicate data. We accept this because cold-start latency matters more than memory cost—for now."

4. Name the Dragons

Instead of:

"Be careful with the date handling code"

Write:

"The parseDate() function looks innocent. It has eaten three afternoons of my life. The issue: it silently coerces invalid dates to the Unix epoch instead of throwing. If you see January 1, 1970 in your output, check your inputs."

Phase 5: Validate and Polish

5.1 Check for Completeness

Does the document answer:

• What does this project do?
• Why does it exist?
• How is it structured?
• What technologies and why?
• Where are the gotchas?
• What can I learn from it?

5.2 Check for Engagement

Does the document:

• Have a hook in the first paragraph?
• Use at least 3 analogies?
• Include specific examples/code snippets?
• Tell stories, not just state facts?
• Have personality (not corporate-speak)?

5.3 Write the File

Write({
  file_path: "[project_root]/FOR_[NAME].md",
  content: generatedDocument
})

Output Calibration

Depth Levels

Shallow (5-10 min read):

• Problem statement
• High-level architecture
• Key technologies
• 2-3 main lessons

Medium (15-20 min read):

• All of shallow
• One deep-dive section
• 3-5 bugs/gotchas
• Best practices
• Engineering philosophy

Deep (30+ min read):

• All of medium
• Multiple deep-dives
• Comprehensive bug history
• Future roadmap
• Cross-references to related systems

Special Cases

For Libraries/Packages

Focus on:

• API design decisions
• Usage patterns (show real examples)
• Performance characteristics
• Migration guides if there are breaking versions

For Infrastructure/DevOps

Focus on:

• Failure modes and recovery
• Scaling characteristics
• Cost implications
• Operational runbooks (in narrative form)

For Data Systems

Focus on:

• Data flow diagrams
• Consistency guarantees (and where they break)
• Schema evolution strategy
• Query patterns that perform well vs poorly

Example Invocations

# Full codebase explanation for yourself
/explain-codebase

# Explain a specific subsystem
/explain-codebase --domain "authentication"

# Create onboarding doc for a teammate
/explain-codebase --name "Sarah" --depth deep

# Explain an external project you're learning
/explain-codebase ~/code/some-open-source-project

References

Load these as needed for specific domains:

• writing-techniques.md — Engagement patterns
• architecture-patterns.md — Common patterns to recognize
• analogy-bank.md — Ready-to-use analogies for common concepts