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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-explorationsegment-pattern-small-multiples.md

≈722 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Faceted Scatter — Segment Patterns Without Overplotting (Vega-Lite)

Best for: comparing the same x/y relationship across segments while keeping each segment visually separate Avoid when: all points can live comfortably in one plot, or the segments need shared trend overlays instead of separate panes Answers: whether each segment follows the same pattern, and which segment behaves differently

{
  "config": { "range": { "category": ["#2b66c4", "#2f9e44", "#f3a33c", "#d1242f", "#7048e8", "#0f9b9b", "#c16f8a", "#7c5a3d"] } },
  "$schema": "https://vega.github.io/schema/vega-lite/v6.json",
  "data": {
    "values": [
      {"segment": "SMB", "risk": 2.1, "value": 3.8},
      {"segment": "SMB", "risk": 3.0, "value": 4.6},
      {"segment": "SMB", "risk": 4.2, "value": 5.7},
      {"segment": "Mid", "risk": 2.8, "value": 5.2},
      {"segment": "Mid", "risk": 4.4, "value": 6.3},
      {"segment": "Mid", "risk": 5.3, "value": 7.1},
      {"segment": "Enterprise", "risk": 3.6, "value": 6.2},
      {"segment": "Enterprise", "risk": 5.0, "value": 7.8},
      {"segment": "Enterprise", "risk": 6.4, "value": 8.6}
    ]
  },
  "title": {"text": "Segment Patterns", "subtitle": "Risk versus value by customer segment", "anchor": "start"},
  "facet": {"field": "segment", "type": "nominal", "columns": 3, "title": null},
  "spec": {
    "width": 180,
    "height": 180,
    "mark": {"type": "point", "filled": true, "size": 85},
    "encoding": {
      "x": {"field": "risk", "type": "quantitative", "scale": {"domain": [0, 7]}, "title": "Risk"},
      "y": {"field": "value", "type": "quantitative", "scale": {"domain": [0, 10]}, "title": "Value"},
      "color": {"field": "segment", "type": "nominal", "legend": null}
    }
  }
}

Data Shape

One row per observation, plus a facet field that splits the shared scatter structure into separate panels.

Key Options

Option Effect
facet Splits the view into comparable small multiples
Shared scale domains Keeps comparison across panels honest
columns Controls how the trellis wraps across the page
Fixed width / height per facet Keeps export layout stable

Pitfalls

  • ❌ Auto-scaling each facet independently → ✅ similar patterns can look misleadingly different
  • ❌ Overlaying segments with too much overplotting → ✅ faceting is the point when separation improves reading
  • ❌ Too many facets in one export → ✅ trellis views need enough area per panel to justify themselves

Alternatives

Variant Use instead
One combined relationship plot scatter-segment-correlation.md
Small distribution panes A faceted histogram or strip-plot spec
Category score grid matrix-service-scorecards.md
<!-- source: Vega-Lite docs (facet / trellis views) + examples gallery Faceting / Small Multiples -->

Source: SKILL.md on GitHub

skilld matched fixed text patterns in SKILL.md and file names. Patterns miss obfuscated code.

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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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