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/documd-visuals

@2672b69
by Markdown Viewermarkdown-viewer/skills3.4k stars
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Create text-driven visuals in Markdown: charts, diagrams, cards, architecture and page layouts. Charts and analytical views (bar, line, pie, heatmap, correlation, regression); reliability and operations (latency, incident, throughput, cycle time, OKR, standup, on-call); product and finance (funnel, retention, revenue, budget); process and workflow (approval, BPMN); software design and behaviour (class, state machine, sequence, C4); dependencies and impact (dependency graph, ER, causality); system architecture as HTML (layer stack, wings, zones, topology, service catalogue, request paths); infrastructure (cloud, Kubernetes, ETL, network, security, IAM, compliance); governance and people (ArchiMate, org chart, hiring); knowledge and planning (mind map, roadmap, Gantt, migration); documents (comparison, SWOT, memo, policy, catalogue, case study). Use when a document needs a diagram, chart or card. Figures render live. Not for slide decks or math notation. Not recommended: mermaid / canvas / drawio / dot.

Use this Skill: https://skilld.dev/gh/markdown-viewer/skills/documd-visuals

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examplesdata-explorationmetric-distribution-small-multiples.md

≈682 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Repeat Histograms — Distribution Across Metrics (Vega-Lite)

Best for: comparing the shape of several numeric fields without overlaying them into one unreadable chart Avoid when: the reader only needs one metric or expects exact raw values rather than distribution shape Answers: how multiple measures differ in spread, concentration, and skew under the same visual grammar

{
  "config": { "range": { "category": ["#2b66c4", "#2f9e44", "#f3a33c", "#d1242f", "#7048e8", "#0f9b9b", "#c16f8a", "#7c5a3d"] } },
  "$schema": "https://vega.github.io/schema/vega-lite/v6.json",
  "title": {"text": "Metric Distributions", "subtitle": "Repeated histograms for latency, queue depth, and retries", "anchor": "start"},
  "data": {
    "values": [
      {"latency": 118, "queue": 22, "retries": 1}, {"latency": 132, "queue": 25, "retries": 1}, {"latency": 145, "queue": 30, "retries": 2},
      {"latency": 151, "queue": 31, "retries": 2}, {"latency": 166, "queue": 36, "retries": 3}, {"latency": 177, "queue": 42, "retries": 4},
      {"latency": 184, "queue": 39, "retries": 3}, {"latency": 196, "queue": 46, "retries": 5}, {"latency": 208, "queue": 51, "retries": 5}
    ]
  },
  "repeat": {"column": ["latency", "queue", "retries"]},
  "spec": {
    "width": 170,
    "height": 180,
    "mark": "bar",
    "encoding": {
      "x": {"field": {"repeat": "column"}, "bin": true, "type": "quantitative", "title": null},
      "y": {"aggregate": "count", "type": "quantitative", "title": "Count"}
    }
  }
}

Data Shape

One row per observation with several numeric fields. The repeat operator projects the same histogram grammar across each selected metric field.

Key Options

Option Effect
repeat.column Reuses one histogram spec across multiple numeric fields
Binned quantitative x Turns each repeated panel into a distribution view
Shared y aggregate Makes the repeated panels comparable as counts
Fixed facet sizes Keeps the export stable and evenly balanced

Pitfalls

  • ❌ Different units with implied comparability → ✅ repeated panels compare shape, not necessarily scale semantics
  • ❌ Too many repeated fields → ✅ small multiples stop working once each panel is too small to read
  • ❌ Overlaying all metrics together → ✅ repeat exists precisely to avoid overplotting different distributions

Alternatives

Variant Use instead
One metric only A single histogram spec
Segment comparison by facet segment-pattern-small-multiples.md
Category distributions release-duration-distribution.md
<!-- source: Vega-Lite docs (repeat / histogram) + examples gallery Repeat & Concatenation -->

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub16d

    This skill provides documentation and examples for creating various visuals in Markdown using engines like ECharts, Vega, PlantUML, and HTML. It recommends using the vendor-owned @markdown-viewer/documd CLI tool for document conversion and verification. The skill itself contains no executable code or malicious patterns.

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    Risk: LOW · No issues

Signed by skilld at 2672b69. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 weeks ago.

Activeupdated 3 weeks ago
Other metadata
compatibility
Figures are text in the Markdown — fenced blocks or bare HTML — and the host viewer renders them live: nothing to pre-render, build or install. Export to html / epub / docx / pdf is optional and needs Node 18+ and Chrome/Chromium, via `npx @markdown-viewer/documd`.

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