eli5

eli5 is a skill for Claude Code, Codex from JAICHANGPARK/workshop-harness. It costs 42 tokens per session (532 once invoked), scanned A, original, MIT.

An explanation aid that describes code, system designs, technical topics, and errors in very simple language using everyday comparisons, short text, and visual diagrams.

In plain words
What is it for?
It is for learning how code or systems work, understanding design choices, diagnosing runtime errors, and creating simple diagrams or explanations for other people.
Why use it?
It makes unfamiliar technical material easier to understand while keeping the basic cause-and-effect relationship accurate.

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/jaichangpark/workshop-harness/eli5
Any agent
npx skills add JAICHANGPARK/workshop-harness --skill eli5
Clone the repo
git clone --depth 1 https://github.com/JAICHANGPARK/workshop-harness

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for eli5

README.md
[![agentmods](https://agentmods.dev/badge/skills/jaichangpark/workshop-harness/eli5.svg)](https://agentmods.dev/skills/jaichangpark/workshop-harness/eli5)
Your own site
<a href="https://agentmods.dev/skills/jaichangpark/workshop-harness/eli5"><img src="https://agentmods.dev/badge/skills/jaichangpark/workshop-harness/eli5.svg" alt="Measured on agentmods" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 532 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 $0.00042 $0.00532
Opus 5 $0.00021 $0.00266
Sonnet 5 $0.00008 $0.00106
Haiku 4.5 $0.00004 $0.00053

Measured 4d ago against content hash 4daf644887f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

eli5 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 4d 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.

skills/eli5/SKILL.md · 57 lines

How it starts

The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ELI5 (Explain Like I'm 5) Skill

Based on the Claude Code Community Plugin specification (eli5@claude-community).

Purpose

Explains complex technical topics, code modules, design trade-offs, and runtime errors in dead-simple terms as if explaining to a 5-year-old child. Focuses on intuitive real-world analogies, visual diagrams, and minimal text rather than dense jargon.


Core Rules

  1. Big Pictures & Visuals First:

    • Always illustrate the explanation with clean diagrams (Mermaid flowcharts/mindmaps or visual artifacts).
    • Use visual components (boxes, arrows, illustrations) rather than long paragraphs of text.
  2. No Technical Jargon:

    • Strip away math formulas, acronyms, and low-level implementation details.
    • Ground every concept in a physical, everyday object (e.g. toy box, library, kitchen, telephone, mail carrier).
  3. Very Few Words:

    • Keep sentences short, conversational, and direct.
    • Avoid walls of text. Use bullet points and callouts.
  4. Preserve the Core Mechanism:

    • Simplicity must never sacrifice accuracy. The explanation must correctly represent the fundamental cause-and-effect relationship under the hood.

Output Structure

When the user asks to explain a concept or runs /eli5 <topic>:

1. The 1-Sentence Analogy

A single sentence comparing the concept to something from daily life.

2. The Visual Picture (Mermaid Diagram)

A simple, colorful flowchart showing how the parts interact.

flowchart LR
    A["Everyday Thing 1"] --> B["Action / Bridge"] --> C["Result / Output"]

3. Step-by-Step Story (3 Simple Steps)

  • Step 1: Where it starts (e.g. "You ask for a toy").
  • Step 2: What happens behind the scenes (e.g. "The helper robot goes to the closet").
  • Step 3: What you get back (e.g. "The robot hands you the toy").

4. What this means in your code / system

A brief 1-2 sentence bridge connecting the analogy back to the user's actual project or terminal error.

Read the full file on GitHub · 57 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. 4d ago First seen · 57 lines · 42 tokens per session scan A 4daf644887f0

Subscribe to this mod's changes

eli5 is a skill published in the GitHub repository JAICHANGPARK/workshop-harness (5 stars, last pushed 3d ago), licensed MIT. It adds 42 tokens to every session and 532 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 2026-08-31.

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