code-explanation

A method for explaining unfamiliar code, starting with what the system does and then moving into its files, modules, functions, and individual lines.

In plain words
What is it for?
It helps create onboarding explanations, document architecture and design choices, walk through complex algorithms, and clarify why particular code behaves as it does.
Why use it?
It reduces misunderstandings when new developers join a project, review code, investigate errors, or work on legacy software.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jeremydev87/codingbuddy/code-explanation
Any agent
npx skills add JeremyDev87/codingbuddy --skill code-explanation
Clone the repo
git clone --depth 1 https://github.com/JeremyDev87/codingbuddy

Made for: Claude Code, Codex.

Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,792 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00037 $0.01792
Opus 5 $0.00018 $0.00896
Sonnet 5 $0.00007 $0.00358
Haiku 4.5 $0.00004 $0.00179

Measured yesterday against content hash 1ab5e9e360fc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-explanation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/rules/.ai-rules/skills/code-explanation/SKILL.md · 264 lines

How it starts

The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Code Explanation

Overview

Understanding code is a prerequisite to improving it. Rushed explanations create misunderstanding that compounds over time.

Core principle: Explain at the right level of abstraction. Start high, drill down only when needed.

Iron Law:

READ BEFORE EXPLAINING. UNDERSTAND BEFORE SIMPLIFYING.

Never explain code you haven't fully read. Never simplify what you haven't fully understood.

When to Use

  • Onboarding new team members to a codebase
  • Code review: explaining design decisions
  • Understanding legacy code before modifying it
  • Explaining an AI agent's recommendations
  • Documenting complex algorithms or patterns
  • Understanding error stack traces

The Five Levels of Explanation

Choose the level based on your audience and purpose:

Level Audience Goal Depth
L1: Bird's Eye Non-technical stakeholders What does this system do? Architecture diagram
L2: Module New developers How is this organized? Module/file structure
L3: Function Developers onboarding What does this code do? Function by function
L4: Line Debugging partners Why is this written this way? Line by line
L5: Algorithm Algorithm review How does this work mathematically? Proof-level

The Explanation Process

Phase 1: Read First

1. Read the entire file/function before explaining anything
2. Identify the core purpose (what problem does this solve?)
3. Note dependencies (what does this require?)
4. Note side effects (what does this change?)
5. Note error handling (what can go wrong?)

Phase 2: Bird's Eye View (Always Start Here)

**What this is:** One sentence describing purpose
**What problem it solves:** The business/technical need
**How it fits:** Where it sits in the larger system
**Key dependencies:** What it relies on
**Key outputs:** What it produces or modifies

Example:

**What this is:** RulesService — file system reader for AI coding rules
**What problem it solves:** Provides a unified interface for reading and searching
  .ai-rules files regardless of directory structure
**How it fits:** Used by McpModule to serve rules via MCP protocol
**Key dependencies:** Node.js fs/promises, glob patterns
**Key outputs:** Array of Rule objects with name, content, and metadata

Read the full file on GitHub · 264 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 264 lines · 37 tokens per session scan A 1ab5e9e360fc

Subscribe to this mod's changes

code-explanation is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 1,792 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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