Borrowing it
Nothing to install: this file belongs to luanmorenommaciel/agentspec. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/luanmorenommaciel/agentspec/main/.claude/skills/visual-explainer/SKILL.mdgit clone --depth 1 https://github.com/luanmorenommaciel/agentspecWrote 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/luanmorenommaciel/agentspec/visual-explainer)<a href="https://agentmods.dev/skills/luanmorenommaciel/agentspec/visual-explainer"><img src="https://agentmods.dev/badge/skills/luanmorenommaciel/agentspec/visual-explainer/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/luanmorenommaciel/agentspec/visual-explainer"><img src="https://agentmods.dev/badge/skills/luanmorenommaciel/agentspec/visual-explainer.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 | $0.00090 | $0.08361 |
| Opus 5.5 | $0.00036 | $0.03344 |
| Sonnet 5.5 | $0.00018 | $0.01672 |
| Haiku 4.5 | $0.00009 | $0.00836 |
Grade A, and why
visual-explainer 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.
This is a copy
91% identical to visual-explainer — 347 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Explainer
Generate self-contained HTML files for technical diagrams, visualizations, and data tables. Always open the result in the browser. Never fall back to ASCII art when this skill is loaded.
Proactive table rendering. When you're about to present tabular data as an ASCII box-drawing table in the terminal (comparisons, audits, feature matrices, status reports, any structured rows/columns), generate an HTML page instead. The threshold: if the table has 4+ rows or 3+ columns, it belongs in the browser. Don't wait for the user to ask — render it as HTML automatically and tell them the file path. You can still include a brief text summary in the chat, but the table itself should be the HTML page.
Available Commands
Detailed prompt templates in .claude/commands/visual-explainer/. In Pi, these are slash commands (/diff-review). In Claude Code, namespaced (/visual-explainer:diff-review). In Codex, use /prompts:diff-review (if installed to ~/.codex/prompts/) or invoke $visual-explainer and describe the workflow.
| Command | What it does |
|---|---|
generate-web-diagram |
Generate an HTML diagram for any topic |
generate-visual-plan |
Generate a visual implementation plan for a feature |
generate-slides |
Generate a magazine-quality slide deck |
diff-review |
Visual diff review with architecture comparison and code review |
plan-review |
Compare a plan against the codebase with risk assessment |
project-recap |
Mental model snapshot for context-switching back to a project |
fact-check |
Verify accuracy of a document against actual code |
share |
Deploy an HTML page to Vercel and get a live URL |
Workflow
1. Think (5 seconds, not 5 minutes)
Before writing HTML, commit to a direction. Don't default to "dark theme with blue accents" every time.
Visual is always default. Even essays, blog posts, and articles get visual treatment — extract structure into cards, diagrams, grids, tables.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/css-patterns.md 43 KB
- references/libraries.md 21 KB
- references/responsive-nav.md 5.7 KB
- references/slide-patterns.md 44 KB
- scripts/share.sh 2.9 KB runs code
- templates/architecture.html 17 KB
- templates/data-table.html 16 KB
- templates/mermaid-flowchart.html 21 KB
- templates/slide-deck.html 35 KB
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 · 475 lines · 90 tokens per session scan A 67331dfad769
visual-explainer is a skill published in the GitHub repository luanmorenommaciel/agentspec (256 stars, last pushed 3d ago), licensed MIT. It adds 90 tokens to every session and 8,361 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 91% identical to visual-explainer, differing in 347 lines, and is treated as a copy.
Other skills, from other repositories
hps-bauhaus
A visual-design fundamentals course for new brand designers — grid, type, color, and the exercises that build the eye. Built as a decision-grade professional training deck for junior designers, new hires.
hps-memphis-pop
A pop-culture retrospective on how 1980s design language shaped today's apps — the scenes, the turning point, and the takeaway. Built as a decision-grade story deck for talk audience, design community.
html-ppt-zhangzara-scatterbrain
A design-school graduation project: a civic wayfinding system for a transit hub — the brief, the process, and the outcome. Built as a decision-grade coursework defense deck for crit panel, faculty.
html-ppt-zhangzara-playful
A retail sales-floor training on consultative selling — the flow, the role-plays, and the daily habit that lifts conversion. Built as a decision-grade professional training deck for store associates, floor managers.
html-ppt-zhangzara-retro-windows
An IT security-awareness training on spotting phishing — the tells, the drill, and what to do in the first 60 seconds. Built as a decision-grade professional training deck for all employees.
frontend-slides
OpenDesign as a worked AI-workflow example: how local agents read your files and design on your desktop — concretely. Built as a decision-grade AI literacy deck for teams new to AI, leadership.