Vizro is an open-source Python toolkit for assembling data visualization applications from low-code configuration. It helps developers create dashboards and multi-page apps from charts, tables, controls, layouts, navigation, and interactions, with optional high-code customization. Catalogue add-ons support working with Vizro projects.
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 mckinsey/vizro --skill wiring-vizro-actionsgit clone --depth 1 https://github.com/mckinsey/vizroWrote 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/mckinsey/vizro/wiring-vizro-actions)<a href="https://agentmods.dev/skills/mckinsey/vizro/wiring-vizro-actions"><img src="https://agentmods.dev/badge/skills/mckinsey/vizro/wiring-vizro-actions/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/mckinsey/vizro/wiring-vizro-actions"><img src="https://agentmods.dev/badge/skills/mckinsey/vizro/wiring-vizro-actions.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 | $0.00086 | $0.01989 |
| Opus 5 | $0.00043 | $0.00994 |
| Sonnet 5 | $0.00017 | $0.00398 |
| Haiku 4.5 | $0.00009 | $0.00199 |
Grade A, and why
wiring-vizro-actions 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wiring Vizro Actions
Core concept: Source → Control → Target
All advanced interactions follow the same shape:
- A source component triggers
va.set_controlwhen the user clicks it. Practical sources arevm.Graphandvm.AgGrid— they carry click-data (column values from the clicked point/cell) that can drive a dynamic filter. (vm.Figure/vm.Button/vm.Cardtechnically supportset_controltoo, but only with a hardcoded literalvalue, so they are not useful for cross-filtering.) set_controlwrites a value into an intermediate control (vm.Filterorvm.Parameter) with an explicitid.- The control updates target components. Filter/Parameter targets are data-bearing components:
vm.Graph,vm.AgGrid,vm.Figure,vm.Table.
The control is always explicit — you do not connect components directly. This makes interactions composable (you can wire multiple sources to the same control, or one source to multiple controls).
Built-in actions
| Action | Purpose | Trigger |
|---|---|---|
va.export_data() |
Download all on-page data as CSV (respects filters) | vm.Button |
va.set_control(control=..., value=...) |
Set the value of a Filter or Parameter | vm.Graph or vm.AgGrid |
import vizro.actions as va. Built-in actions are passed directly into actions= — wrapping them in vm.Action raises an error (deliberate: built-ins have their own predefined inputs/outputs and would conflict with vm.Action's).
# Correct
vm.Button(text="Export data", actions=va.export_data())
vm.Graph(actions=va.set_control(control="region_filter", value="y"))
# Wrong — raises an exception
vm.Graph(actions=[vm.Action(function=va.set_control(...))])
Named interaction patterns
Match data shape + user need to a pattern. Full details (when-to-use, wireframes, spec entries, code) in actions-reference.md.
| # | Pattern | When to use | Key mechanic |
|---|---|---|---|
| 1 | Hierarchical Drill-Down (cross-page) | 2–3 level hierarchy where detail needs a dedicated page | cross-filter + show_in_url=True + back button + export |
| 2 | Single-Page Drill-Down (container) | 2-level hierarchy where detail fits in a container | cross-filter into a container |
| 3 | Comparison Spotlight (cross-highlight) | Compare one entity against many without removing context | custom chart with highlight_X + invisible Parameter |
| 4 | Multi-Dimensional Slice | 2+ categorical dimensions (e.g. day × time heatmap) | actions chain → multiple Filters |
| 5 | Data Export | Analyst persona needs the filtered data downloaded | vm.Button + va.export_data() |
What ships with it
1 file 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.
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 · 168 lines · 86 tokens per session scan A 6fdcf7b25045
wiring-vizro-actions is a skill published in the GitHub repository mckinsey/vizro (3,789 stars, last pushed today), licensed Apache-2.0. It adds 86 tokens to every session and 1,989 once invoked, about $0.0004 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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