/documd-visuals

by Markdown Viewermarkdown-viewer/skills3.4k stars

192

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.

251 files
1.3 MB
Updated 3 weeks ago
GitHub
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Use this Skill: https://skilld.dev/gh/markdown-viewer/skills/documd-visuals

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Edit a local copy. It keeps the author and licence.

enginesplantuml-stencilsgcp.md

5.2 KB raw

≈1.3k tokens on demand. Your agent reads this file only when SKILL.md points to it.

GCP Stencils

Stencil library: mxgraph.gcp.*

Total: 66 stencils

Style hints

66 shape(s) need fillColor+strokeColor

Shape	Required Styles
`mxgraph.gcp.big_data.bigquery`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.cloud_dataflow`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.cloud_datalab`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.cloud_dataprep`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.cloud_dataproc`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.cloud_pubsub`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.data_studio`	`fillColor`+`strokeColor`
`mxgraph.gcp.big_data.genomics`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.app_engine`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.cloud_functions`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.compute_engine`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.container_engine`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.container_optimized_os`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.container_registry`	`fillColor`+`strokeColor`
`mxgraph.gcp.compute.gpu`	`fillColor`+`strokeColor`
`mxgraph.gcp.developer_tools.cloud_tools_for_powershell`	`fillColor`+`strokeColor`
`mxgraph.gcp.developer_tools.cloud_tools_for_visual_studio`	`fillColor`+`strokeColor`
`mxgraph.gcp.developer_tools.deployment_manager`	`fillColor`+`strokeColor`
`mxgraph.gcp.extras.blue_hexagon`	`fillColor`+`strokeColor`
`mxgraph.gcp.extras.generic_gcp`	`fillColor`+`strokeColor`
`mxgraph.gcp.extras.google_cloud_platform`	`fillColor`+`strokeColor`
`mxgraph.gcp.extras.google_cloud_platform_lockup`	`fillColor`+`strokeColor`
`mxgraph.gcp.extras.prediction_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.identity_and_security.beyondcorp`	`fillColor`+`strokeColor`
`mxgraph.gcp.identity_and_security.cloud_data_loss_prevention_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.identity_and_security.cloud_iam`	`fillColor`+`strokeColor`
`mxgraph.gcp.identity_and_security.cloud_identity_aware_proxy`	`fillColor`+`strokeColor`
`mxgraph.gcp.identity_and_security.cloud_platform_security`	`fillColor`+`strokeColor`
`mxgraph.gcp.identity_and_security.security_key_enforcement`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.cloud_machine_learning`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.cloud_video_intelligence_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.jobs_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.natural_language_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.speech_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.translation_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.machine_learning.vision_api`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.cloud_apis`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.cloud_endpoints`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.debugger`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.deployment_manager`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.error_reporting`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.logging`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.monitoring`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.stackdriver`	`fillColor`+`strokeColor`
`mxgraph.gcp.management_tools.trace`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_cdn`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_dns`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_external_ip_addresses`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_firewall_rules`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_interconnect`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_load_balancing`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_network`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_partner_interconnect`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_router`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_routes`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_virtual_network`	`fillColor`+`strokeColor`
`mxgraph.gcp.networking.cloud_vpn`	`fillColor`+`strokeColor`
`mxgraph.gcp.product_cards.close`	`fillColor`+`strokeColor`
`mxgraph.gcp.product_cards.disk`	`fillColor`+`strokeColor`
`mxgraph.gcp.product_cards.standard_machine`	`fillColor`+`strokeColor`
`mxgraph.gcp.storage_databases.cloud_bigtable`	`fillColor`+`strokeColor`
`mxgraph.gcp.storage_databases.cloud_datastore`	`fillColor`+`strokeColor`
`mxgraph.gcp.storage_databases.cloud_spanner`	`fillColor`+`strokeColor`
`mxgraph.gcp.storage_databases.cloud_sql`	`fillColor`+`strokeColor`
`mxgraph.gcp.storage_databases.cloud_storage`	`fillColor`+`strokeColor`
`mxgraph.gcp.storage_databases.persistent_disk`	`fillColor`+`strokeColor`

PlantUML Usage

@startuml
mxgraph.gcp.big_data.bigquery "bigquery" as bigquery
@enduml

Source: SKILL.md on GitHub

Skill behaviors

Installs or runs packages
SKILL.md:144, SKILL.md:153

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

skilld run checks every file with the same patterns. It asks for approval before it loads a Skill with a behavior marked Needs approval.

Third-party checks

No alerts16d3 checks · Risk SAFE

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.
Socket16d
No alerts
Snyk16d
Risk: LOW · No issues

Provenance

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

Capability

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`.