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 MarcSkovMadsen/holoviz-mcp --skill panelgit clone --depth 1 https://github.com/MarcSkovMadsen/holoviz-mcpWrote 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/marcskovmadsen/holoviz-mcp/panel)<a href="https://agentmods.dev/skills/marcskovmadsen/holoviz-mcp/panel"><img src="https://agentmods.dev/badge/skills/marcskovmadsen/holoviz-mcp/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/marcskovmadsen/holoviz-mcp/panel"><img src="https://agentmods.dev/badge/skills/marcskovmadsen/holoviz-mcp/panel.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 | $0.00100 | $0.06655 |
| Opus 5 | $0.00050 | $0.03327 |
| Sonnet 5 | $0.00020 | $0.01331 |
| Haiku 4.5 | $0.00010 | $0.00666 |
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 12d 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 — 688 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Panel Development Skills
This document provides best practices for developing dashboards and data apps with HoloViz Panel in Python .py files.
Please develop as an Expert Python and Panel Developer developing advanced data-driven, analytics and testable dashboards and analytics apps would do. Keep the code short, concise, documented, testable and professional.
Dependencies
Core dependencies provided with the panel Python package:
- panel: Core application framework
- param: A declarative approach to creating classes with typed, validated, and documented parameters. Fundamental to Panel's reactive programming model.
Optional panel-extensions:
- panel-material-ui: Modern Material UI components. To replace the panel native widgets within the next two years.
- panel-graphic-walker: Modern Tableau like interface. Can offload computations to the server and thus scale to large datasets.
Optional dependencies from the HoloViz Ecosystem:
- colorcet: Perceptually uniform colormaps collection. Best for: scientific visualization requiring accurate color representation, avoiding rainbow colormaps, accessible color schemes. Integrates with hvPlot, HoloViews, Matplotlib, Bokeh.
- datashader: Renders large datasets (millions+ points) into images for visualization. Best for: big data visualization, geospatial datasets, scatter plots with millions of points, heatmaps of dense data. Requires hvPlot or HoloViews as frontend.
- geoviews: Geographic data visualization with map projections and tile sources. Best for: geographic/geospatial plots, map-based dashboards, when you need coordinate systems and projections. Built on HoloViews, works seamlessly with hvPlot.
- holoviews: Declarative data visualization library with composable elements. Best for: complex multi-layered plots, advanced interactivity (linked brushing, selection), when you need fine control over plot composition, scientific visualizations. More powerful but steeper learning curve than hvPlot.
- holoviz-mcp: Model Context Protocol server for HoloViz ecosystem. Provides access to detailed documentation, component search and agent skills.
- hvplot: High-level plotting API with Pandas
.plot()-like syntax. Best for: quick exploratory visualizations, interactive plots from DataFrames/Xarray, when you want interactivity without verbose code. Built on HoloViews. - hvsampledata: Shared datasets for the HoloViz projects.
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.
- 12d ago First seen · 688 lines · 100 tokens per session scan A b2d9c9636db9
panel is a skill published in the GitHub repository MarcSkovMadsen/holoviz-mcp (34 stars, last pushed 11d ago), licensed BSD-3-Clause. It adds 100 tokens to every session and 6,655 once invoked, about $0.0005 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.
Other skills, from other repositories
dataviz-mcp
Show Python visualizations live in the browser with the dataviz-mcp MCP tools (show, screenshot). Use when those tools are available and the user asks to display, plot, chart, or visualize anything. Do not use for apps the user serves themselves with panel serve.
build-with-tinybase
Scaffold, extend, and verify reactive local-first JavaScript or TypeScript applications with TinyBase. Use when choosing TinyBase for in-memory tabular or key-value state, generating an app with create-tinybase, adding schemas or UI bindings, configuring browser or database persistence, configuring MergeableStore…
portaljs-add-map
Render a GeoJSON dataset on an interactive Leaflet map in the Views section of a dataset's showcase. Installs react-leaflet and a Map component, then renders the map for the chosen dataset. Use when a dataset's data is geographic and a map view is needed alongside the showcase's default metadata and download.
portaljs-add-chart
Add a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.
reimagine-it-extract
Emit the content signals reimagine-it reads from an HTML file — title, anchors, proper nouns, dates, numbers, emails, links, source hex colors, and the derived palette — as JSON without generating a redesign. Use when the user says /reimagine-it extract, "what does the engine see in this page", "extract the palette"…
malloy-html-data-apps
Build or modify an in-package HTML data app for a Malloy Publisher package (a public/ directory the package serves). Use when the user wants a hand-authored HTML dashboard or web page backed by a package's Malloy models, with no build step.