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.
npx skills add JeremyDev87/codingbuddy --skill code-explanationgit clone --depth 1 https://github.com/JeremyDev87/codingbuddyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jeremydev87/codingbuddy/code-explanation)<a href="https://agentmods.dev/skills/jeremydev87/codingbuddy/code-explanation"><img src="https://agentmods.dev/badge/skills/jeremydev87/codingbuddy/code-explanation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jeremydev87/codingbuddy/code-explanation"><img src="https://agentmods.dev/badge/skills/jeremydev87/codingbuddy/code-explanation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00037 | $0.01792 |
| Opus 5.5 | $0.00015 | $0.00717 |
| Sonnet 5.5 | $0.00007 | $0.00358 |
| Haiku 4.5 | $0.00004 | $0.00179 |
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 1mo ago.
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.
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
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.
- 1mo ago First seen · 264 lines · 37 tokens per session scan A 1ab5e9e360fc
code-explanation is a skill published in the GitHub repository JeremyDev87/codingbuddy (31 stars, last pushed 6mo ago), licensed MIT. It adds 37 tokens to every session and 1,792 once invoked, about $0.0001 per session on Opus 5.5. 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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