Gradio is a Python package for building web interfaces around machine learning models, APIs, or ordinary Python functions. It is used by developers and data scientists to create and share interactive demos without writing frontend code.
Borrowing it
Nothing to install: this file belongs to gradio-app/gradio. 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/gradio-app/gradio/main/.agents/skills/gradio-themes/SKILL.mdgit clone --depth 1 https://github.com/gradio-app/gradioWrote 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/gradio-app/gradio/gradio-themes)<a href="https://agentmods.dev/skills/gradio-app/gradio/gradio-themes"><img src="https://agentmods.dev/badge/skills/gradio-app/gradio/gradio-themes/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/gradio-app/gradio/gradio-themes"><img src="https://agentmods.dev/badge/skills/gradio-app/gradio/gradio-themes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00039 | $0.03558 |
| Opus 5 | $0.00019 | $0.01779 |
| Sonnet 5 | $0.00008 | $0.00712 |
| Haiku 4.5 | $0.00004 | $0.00356 |
Grade A, and why
gradio-themes 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 11d 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gradio Theme Building
You are an expert at building Gradio themes. Themes control the entire visual identity of a Gradio app — colours, typography, spacing, shadows, and dark mode — through Python classes that compile to CSS custom properties.
Core Principles
-
Text contrast is non-negotiable. Every text element must be readable against its actual background — body text, label text on coloured label fills, button text on button fills, placeholder text, selected checkbox text, error text, link text. A beautiful theme that can't be read is useless. Audit every text/background pair before shipping.
-
Dark mode is independently designed. Never auto-invert light values. Every
_darkvariable should be intentionally chosen for contrast and readability on dark backgrounds. Specifically:- Reduce font weight slightly on dark (350 instead of 400) — light text on dark reads heavier
- Desaturate accents — high chroma at high lightness looks garish
- Use lighter surfaces for elevation, not heavier shadows
- Never use pure black
#000— use#0a0a14-ish dark with a subtle hue cast
-
Commit to an aesthetic direction. Bold maximalism and refined minimalism both work — what fails is half-commitment. Pick one tone (editorial, brutal, glass, retro, organic, playful, industrial...) and execute every variable in service of it.
-
Use variable references (
*name) for consistency. When one value should track another, reference it. This keeps themes maintainable and lets users customise constructor params (hues, sizes) and have changes cascade. -
Test both modes. Always verify light AND dark for body, blocks, inputs, buttons, labels, checkboxes, tables, focus states, hover states, selected states.
Aesthetic Quality
Technical correctness isn't enough. A theme can have every variable set perfectly and still look generic. Apply these checks:
The "AI Slop" Test
If you showed this theme to someone and said "AI made this," would they immediately believe you? If yes, that's the problem. A distinctive theme makes someone ask "how was this made?" not "which AI made this?"
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.
- 11d ago First seen · 266 lines · 39 tokens per session scan A b6d63cc3fbc0
gradio-themes is a skill published in the GitHub repository gradio-app/gradio (43,507 stars, last pushed today), licensed Apache-2.0. It adds 39 tokens to every session and 3,558 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 2026-08-30.
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