Shiny for Python is a Python framework for building interactive web applications and data visualizations with reactive behavior. Data scientists and Python developers use it for prototypes as well as larger applications. Its bundled agent skills provide coding agents with Shiny documentation so they can create better Shiny applications.
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 skills add posit-dev/py-shiny --skill shiny-for-pythongit clone --depth 1 https://github.com/posit-dev/py-shinyWrote 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/posit-dev/py-shiny/shiny-for-python)<a href="https://agentmods.dev/skills/posit-dev/py-shiny/shiny-for-python"><img src="https://agentmods.dev/badge/skills/posit-dev/py-shiny/shiny-for-python/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/posit-dev/py-shiny/shiny-for-python"><img src="https://agentmods.dev/badge/skills/posit-dev/py-shiny/shiny-for-python.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00218 | $0.01498 |
| Opus 5.5 | $0.00087 | $0.00599 |
| Sonnet 5.5 | $0.00044 | $0.00300 |
| Haiku 4.5 | $0.00022 | $0.00150 |
Grade A, and why
shiny-for-python 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 2d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Shiny for Python
Shiny for Python (py-shiny) builds reactive web apps in pure Python. Two modes:
Core (an explicit app_ui object plus a server(input, output, session)
function) and Express (top-level code in the app file is the UI, with
outputs defined inline). The reactive graph is the engine: reading a reactive
source (input.x(), a reactive.value, a @reactive.calc) inside a reactive
context registers a dependency, so changing that source re-runs everything that
read it — you never call outputs or schedule updates yourself.
This skill is an index. Find your task below and read the linked reference file before writing code for that area.
Foundations
| Topic | Use when | Reference |
|---|---|---|
| Reactivity | A value should recompute or an output update as inputs change; choosing between calc / effect / value; req, isolate, timers, polling, setting values from background tasks |
references/reactivity.md |
| Express mode | Writing or converting an Express app (from shiny.express import ...); context-manager layout; page_opts, @expressify |
references/express.md |
| Modules (Core) | A reusable, repeatable UI+server component in a Core app; avoiding input/output id collisions across copies | references/modules-core.md |
| Modules (Express) | The same reusable-component need in an Express app, via the single @module decorator |
references/modules-express.md |
| Session lifecycle | Per-session cleanup (on_ended), reading request headers/cookies/URL, flush hooks, per-session routes |
references/session-lifecycle.md |
Dashboard building
| Topic | Use when | Reference |
|---|---|---|
| Dashboard design | Turning a dataset or brief into a polished analytical dashboard; planning information hierarchy, shared filters, responsive layout, empty states, and the final visual/functional quality pass | references/dashboard-design.md |
| Dashboard components | Composing cards, KPI value boxes, local card toolbars, accessible icons, tooltips, and popovers | references/dashboard-components.md |
| Interactive charts | Rendering Plotly charts with shinywidgets; choosing chart forms, applying a coherent visual system, formatting hover/data labels, and handling empty data | references/interactive-charts.md |
| Maps | Choosing and rendering a geographic widget; cleaning coordinates, avoiding overplotting, and selecting Plotly, ipyleaflet, or lonboard by interaction and scale | references/maps.md |
What ships with it
27 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/bookmarking.md 6.2 KB
- references/chat.md 5.7 KB
- references/custom-components.md 5.6 KB
- references/custom-renderers.md 5.7 KB
- references/dashboard-components.md 5.4 KB
- references/dashboard-design.md 6.0 KB
- references/data-frames.md 5.4 KB
- references/debugging.md 4.7 KB
- references/dynamic-ui.md 5.3 KB
- references/express.md 5.9 KB
- references/extended-tasks.md 5.2 KB
- references/feedback.md 5.6 KB
- references/files.md 5.3 KB
- references/interactive-charts.md 5.0 KB
- references/layouts.md 5.2 KB
- references/maps.md 6.2 KB
- references/markdown-streaming.md 4.6 KB
- references/modules-core.md 6.0 KB
- references/modules-express.md 3.3 KB
- references/navigation.md 5.7 KB
- references/otel.md 5.6 KB
- references/plots.md 5.4 KB
- references/reactivity.md 7.4 KB
- references/session-lifecycle.md 6.8 KB
- references/test-server.md 7.7 KB
- references/testing.md 6.4 KB
- references/theming.md 6.4 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.
- 2d ago Changed 14bcbd67ba0e
- 1mo ago Changed ec862421b336
- 1mo ago Changed · +1 lines · +9 tokens per session 90f368a80b53
- 1mo ago First seen · 84 lines · 209 tokens per session scan A 9299962ea6d1
shiny-for-python is a skill published in the GitHub repository posit-dev/py-shiny (1,762 stars, last pushed yesterday), licensed MIT. It adds 218 tokens to every session and 1,498 once invoked, about $0.0009 per session on Opus 5.5. 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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