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 writing-vizro-yamlgit 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/writing-vizro-yaml)<a href="https://agentmods.dev/skills/mckinsey/vizro/writing-vizro-yaml"><img src="https://agentmods.dev/badge/skills/mckinsey/vizro/writing-vizro-yaml/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/writing-vizro-yaml"><img src="https://agentmods.dev/badge/skills/mckinsey/vizro/writing-vizro-yaml.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 | $0.00066 | $0.00776 |
| Opus 5 | $0.00033 | $0.00388 |
| Sonnet 5 | $0.00013 | $0.00155 |
| Haiku 4.5 | $0.00007 | $0.00078 |
Grade A, and why
writing-vizro-yaml 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 13d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Vizro YAML & Component Reference
Critical Mistakes to Avoid
Each mistake below is expanded with code examples and fixes in yaml-reference.md.
@capture("graph")receives a DataFrame — usedata_framedirectly; never re-lookup viadata_manager[data_frame](causes blank charts).data_manageris not subscriptable — pre-process on raw DataFrame, then register.- Custom
_target_needs module prefix —_target_: custom_charts.my_chart, not_target_: my_chart. type: figurehas notitlefield — KPI titles go in_target_: kpi_cardargs.type: ag_gridrequires_target_: dash_ag_grid.- Parameter targets — format:
"component_id.argument_name", not"component_id.figure". - Quote YAML special chars in column names —
column: "Version #"(unquoted#starts a comment). - Filter
targets:— omit when you want to apply it to all components on the page whose data source includes defined filtercolumn. - Grid must be rectangular — same component index must span same columns in every row.
- Column type consistency — filter column must have same dtype across all targeted datasets.
Quick Patterns
# Standard chart (scatter — no aggregation needed, each row is one point)
- figure:
_target_: scatter
data_frame: sales_data
x: units
y: revenue
type: graph
title: Revenue vs Units
# KPI card (title inside figure args, NOT on component)
- figure:
_target_: kpi_card
data_frame: kpi_data
value_column: Revenue
title: Total Revenue
value_format: "${value:,.0f}"
type: figure
# AG Grid table
- figure:
_target_: dash_ag_grid
data_frame: sales_data
type: ag_grid
title: Sales Data
# Filter with targets
controls:
- column: region
targets: [chart_1, chart_2]
type: filter
Key Imports
import vizro.models as vm
from vizro import Vizro
import vizro.plotly.express as px
from vizro.tables import dash_ag_grid
from vizro.figures import kpi_card, kpi_card_reference
from vizro.models.types import capture
from vizro.managers import data_manager
from vizro.themes import palettes, colors
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.
- 13d ago First seen · 83 lines · 66 tokens per session scan A 17d1db43111c
writing-vizro-yaml is a skill published in the GitHub repository mckinsey/vizro (3,789 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 776 once invoked, about $0.0003 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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