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 agentmods add skills/ginlix-ai/langalpha/inline-widgetnpx skills add ginlix-ai/LangAlpha --skill inline-widgetgit clone --depth 1 https://github.com/ginlix-ai/LangAlphaWhat 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 | $0.00021 | $0.03331 |
| Opus 5 | $0.00010 | $0.01665 |
| Sonnet 5 | $0.00004 | $0.00666 |
| Haiku 4.5 | $0.00002 | $0.00333 |
Grade A, and why
inline-widget 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 3d 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 — 311 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inline Widget
Render interactive HTML/SVG widgets directly inside the chat conversation using ShowWidget. Widgets appear inline between text — no sandbox, no preview URL, no side panel. They run JavaScript, so lean into making them interactive and explorable where it helps — something the user can sort, filter, toggle, and hover over, not just a static picture.
When to Use
- User wants a quick visualization embedded in the conversation (chart, metric card, data table)
- The visualization is self-contained — all data is embedded in the HTML, no server needed
- User wants interactivity within the chat: buttons, toggles, hover effects, animated charts
- The output is a single view — not a multi-page app or dashboard that needs routing
Use interactive-dashboard instead if: User needs a multi-page web app, server-side data, live data refresh, or complex interactivity requiring React/FastAPI.
Read .agents/skills/ui-design/SKILL.md for design quality — its color discipline, chart restraint, and anti-slop principles apply here too. Its font pairings and type scale, though, are for full documents; a widget sits on the chat surface, so use the host-font typography rules below instead.
ShowWidget API
ShowWidget(html: str, title: str | None = None, data_files: list[str] | None = None)
html: Raw HTML fragment — no<!DOCTYPE>,<html>,<head>, or<body>tagstitle: Optional metadata (not displayed to user)data_files: Optional list of sandbox file paths to make available aswindow.__WIDGET_DATA__
The HTML is rendered in a sandboxed iframe with:
- CDN libraries:
cdnjs.cloudflare.com,cdn.jsdelivr.net,unpkg.com,esm.sh - CSS theme variables: automatically injected (see Theme section)
sendPrompt('text'): global function to trigger follow-up chat messageswindow.__WIDGET_DATA__: dict of filename→content for files passed viadata_files- No network to non-CDN origins:
fetch()/XMLHttpRequestto arbitrary URLs are blocked by CSP — only CDN domains (cdnjs, jsdelivr, unpkg, esm.sh) are allowed. Usedata_filesfor sandbox files, or embed small data directly in HTML
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.
- 3d ago First seen · 311 lines · 21 tokens per session scan A f675842f7822
inline-widget is a skill published in the GitHub repository ginlix-ai/LangAlpha (1,718 stars, last pushed yesterday), licensed Apache-2.0. It adds 21 tokens to every session and 3,331 once invoked, about $0.0001 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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