Claude Code's viral ELI5 skill turns any topic into a visual HTML explainer

What the ELI5 skill does

According to a dev.to walkthrough (originally published in Japanese on EdgeHUB), typing /eli5 followed by a topic in Claude Code produces a single HTML artifact rather than an ordinary chat reply. Three constraints shape the output: everything lives in one standalone artifact, text is kept to a minimum, and structure is conveyed through large visuals instead of paragraphs.

The skill went viral in August 2026 after Anthropic's own developers mentioned they use it internally, the article notes. It was published by Thariq Shihipar of the Claude Code team, announced on X on August 21, 2026, and is distributed through the community marketplace under anthropics/claude-plugins-community. The plugin itself is free under the MIT license, though Claude Code usage still bills against your existing plan.

The name oversells the simplicity

One detail the dev.to piece highlights is a deliberate mismatch inside the skill's SKILL.md. The description field, which controls when the skill triggers, still frames it as explaining a topic "like I'm a 5 year old." The body text, which actually drives the model, asks it to explain to "someone who knows nothing about this topic."

That gap is intentional. Writing for a literal five-year-old's vocabulary degrades accuracy, so the prompt was tuned to strip out assumed background knowledge rather than simplify the language to a child's level. In practice, output assumes zero familiarity with the subject but does not dumb down the technical substance.

How to install and use it

Setup takes two commands inside Claude Code:

claude plugin marketplace add anthropics/claude-plugins-community claude plugin install eli5@claude-community

Running claude plugin list should confirm the install, showing eli5@claude-community at version 1.0.0 with user scope and an enabled status.

From there, usage is the slash command plus whatever you want explained, such as /eli5 how does RAG actually work or /eli5 how does auth work in this project. One practical tip from the writeup: without extra prompting, the skill sometimes generates fewer diagrams than you would want. Appending an explicit requirement, such as asking for at least three SVG diagrams, makes the visual output more consistent.

A sample run on RAG

The author tested the skill on retrieval-augmented generation, requesting multiple SVG diagrams and a flowchart of the full pipeline. The result compressed RAG into four steps: gather documents, split them into small chunks, find the chunks closest in meaning to the question, and have the model read those chunks and write an answer — all rendered with emoji and short phrases on a single screen.

The point, the article stresses, is orientation. The output exists to build an initial mental model of a mechanism, not to serve as an exact specification.

Where it helps and where it falls short

The writeup identifies four good fits: distilling how an AI system works into one shareable slide for internal proposals or client materials; offering newcomers a visual overview of auth flows or module structure before they dig into the code; laying out incident retrospectives in chronological order, from where a problem started to what it touched; and self-checking — a failure to sketch a concept visually usually marks the part you have not fully absorbed.

It is a poor fit for anything requiring precision: verifying exact specs, numbers or conditional branches, checking edge cases and boundary conditions, auditing security, or actually fixing code. The recommended pattern is to get the big picture from ELI5, then switch to regular Claude Code prompts or official documentation for the details.

One caveat worth carrying forward: the article reflects Claude Code's behavior as of August 2026, and the tool changes frequently, so command syntax may not match current documentation.

Why it matters

ELI5 points at where agentic coding tools are heading: beyond generating code, they can generate the communication artifacts around it — onboarding material, architecture summaries, incident timelines. As teams adopt agentic tools, the bottleneck often shifts from writing code to explaining systems to stakeholders and new hires, and a one-command visual explainer addresses that directly. The SKILL.md mismatch is also a useful lesson for anyone authoring their own skills: the trigger description and the instruction body serve different purposes, and tuning them separately is worth doing deliberately.