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 holoviz-dev/holoviz-skills --skill panelgit clone --depth 1 https://github.com/holoviz-dev/holoviz-skillsWrote 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/holoviz-dev/holoviz-skills/panel)<a href="https://agentmods.dev/skills/holoviz-dev/holoviz-skills/panel"><img src="https://agentmods.dev/badge/skills/holoviz-dev/holoviz-skills/panel/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/holoviz-dev/holoviz-skills/panel"><img src="https://agentmods.dev/badge/skills/holoviz-dev/holoviz-skills/panel.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 | $0.00049 | $0.03720 |
| Opus 5 | $0.00024 | $0.01860 |
| Sonnet 5 | $0.00010 | $0.00744 |
| Haiku 4.5 | $0.00005 | $0.00372 |
Grade A, and why
panel 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 10d 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Panel
Panel is a Python library for building interactive dashboards, data apps, and tools entirely in Python — no JavaScript required. It connects widgets to plots, tables, and text with reactive callbacks, and serves the result as a web application.
Always use a pn.viewable.Viewer class to structure apps. This keeps state, layout, and logic organized and avoids flickering from recreated components. Once an app outgrows one class — multiple views over shared data, state several components touch — split it into composable classes (see Designing Panel Architecture).
Contents
- References — iterative development, Material UI, plotting, data storytelling, custom components, React shells, Playwright testing, app structure & scaling, review
- Lookup — component docs URLs and site search
- Viewer Class Pattern
- Widgets and Extensions
- Defaults
- Templates and Layouts
- Serving Workflow
- Performance
References
Read these for specialized topics. Each is a standalone document you can load on demand.
- Iterating on Panel Apps — pre-flight lint, serve with logging, panel-live-server MCP tools, live-browser layout lint, Bokeh plot-model inspection, startup benchmarking, screenshot with Playwright, review and debug agentic loop
- Designing Panel Architecture — composing larger apps (State/DataStore/View/App,
param.ClassSelector, cross-object@param.depends,from_data,pn.rx) and runtime/scale (per-session model,pn.statescheduling, URL state sync, generator streaming, caching tiers,nthreads, profiling) - Building Custom Components — Python-vs-JS decision ladder; pure-Python
Viewer/PyComponent; JSComponent, ReactComponent, AnyWidgetComponent, MaterialUIComponent; CDN selection, event handling, state sync lifecycle - Wrapping React Apps — making an existing React/JSX UI the whole app: shell/app class split,
model.useStateas the only transport,Childembedding of Panel components, request/response param pairs, shadow-DOM CSS rules,_importmapexternals,panel compileand the dev-vs-production bundle trap - Using Material UI — building pmui apps (
pmui.Page,Container/Gridlayouts, centering, component gotchas) and theming (theme_configpalette, typography, icons, brand assets, chart theming) - Migrating to Material UI — converting an existing plain-Panel app to pmui: template→Page, widget swaps, pane/interaction upgrades, what to leave alone
- Converting Designs to Material UI — workflow for turning a screenshot/design/React app into a pmui app: capture references, map to components, build component-first with mock data, assemble, theme last
- Plotting in Panel — embedding plots from any library: HoloViews/hvPlot (DynamicMap zoom/pan, responsive sizing), Matplotlib, Plotly, ECharts, Bokeh toolbar tools
- Data Storytelling — assembling explanatory charts into a scrollable editorial article (pmui masthead, narrow reading column, prose-then-chart rhythm, one visual family); see
examples/graphic_story.py - Using Tabulator —
add_filterwith widgets, checkbox selection, row content, function-based filtering - Using Pytest Playwright —
serve_component/wait_untilutilities, JS↔Python sync tests, complete test patterns for custom components - Reviewing Panel Apps — anti-pattern checklist for code review: flickering, missing hold, watcher gaps, reactive-wiring priority, from_param super() ordering, mutation bugs
- Troubleshooting Panel Apps — symptom→cause→fix for apps that serve but misbehave silently: init ordering, dead-app, blank Page, responsive/spinner issues, version & deprecation diagnosis
What ships with it
20 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.
- building-custom-components.md 16 KB
- converting-designs-to-material-ui.md 5.9 KB
- data-storytelling.md 2.0 KB
- designing-panel-architecture.md 16 KB
- examples/dashboard.py 21 KB runs code
- examples/graphic_story.py 8.5 KB runs code
- examples/wizard.py 20 KB runs code
- iterating-on-panel-apps.md 21 KB
- migrating-to-material-ui.md 15 KB
- plotting-in-panel.md 12 KB
- reviewing-panel-apps.md 10.0 KB
- scripts/layout_lint.py 17 KB runs code
- scripts/preflight.py 18 KB runs code
- scripts/test_layout_lint.py 13 KB runs code
- scripts/test_preflight.py 9.7 KB runs code
- troubleshooting-panel-apps.md 11 KB
- using-material-ui.md 28 KB
- using-pytest-playwright.md 5.0 KB
- using-tabulator.md 5.3 KB
- wrapping-react-apps.md 13 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.
- 10d ago First seen · 161 lines · 49 tokens per session scan A 1a633e7429f6
panel is a skill published in the GitHub repository holoviz-dev/holoviz-skills (5 stars, last pushed yesterday), licensed BSD-3-Clause. It adds 49 tokens to every session and 3,720 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 2026-08-31.
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