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diagrams-as-code skill

/Skills/diagrams-as-code

This skill helps you create and refine diagrams of cloud infrastructure using Python diagrams library, producing ready-to-share images.

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---
name: diagrams-as-code
description: Use only when creating architecture diagrams with Python's `diagrams` library (mingrammer/diagrams).
allowed-tools: Bash(python3 *) Bash(uv *) Bash(pip install *) Bash(command -v *) Bash(brew install *) Read Write Edit Glob Grep
---

# Diagrams as Code

Generate architecture and infrastructure diagrams using the Python `diagrams` library. Diagrams are Python scripts that render to image files via Graphviz.

## Workflow

1. **Check prerequisites** - verify graphviz and diagrams are installed
2. **Write the diagram script** to a `.py` file in the user's working directory
3. **Run it** with `python3 <file>.py`
4. **Report the output path** to the user (image appears in working directory)

### Prerequisites check

```bash
command -v dot >/dev/null || brew install graphviz
uv pip install --system diagrams 2>/dev/null || pip install diagrams
```

Without graphviz, the script fails with a cryptic error. Always verify first.

## Core API

### Diagram context manager

```python
from diagrams import Diagram

with Diagram(
    name="Title",           # used as default filename (slugified)
    filename="output",      # override filename (no extension)
    direction="LR",         # LR | RL | TB | BT
    curvestyle="spline",    # spline | ortho | curved | polyline
    outformat="png",        # png | jpg | svg | pdf | dot (or list)
    show=False,             # ALWAYS False - prevents auto-opening
    strict=False,           # merge duplicate edges
    autolabel=False,        # prefix labels with provider/type
    graph_attr={},          # graphviz graph attributes
    node_attr={},           # graphviz node attributes
    edge_attr={},           # graphviz edge attributes
):
    ...
```

Always set `show=False` so the script runs non-interactively.

### Nodes

Import from `diagrams.<provider>.<category>`:

```python
from diagrams.aws.compute import EC2, Lambda, ECS
from diagrams.aws.database import RDS, Aurora
from diagrams.aws.network import ELB, Route53, CloudFront
from diagrams.k8s.compute import Pod, Deployment
from diagrams.onprem.database import PostgreSQL, MySQL
from diagrams.onprem.network import Nginx
```

See `references/providers.md` for the full provider and category listing with common node names.

### Data flow operators

```python
ELB("lb") >> EC2("web") >> RDS("db")    # left to right
RDS("db") << EC2("web")                  # right to left
RDS("primary") - RDS("replica")           # undirected
ELB("lb") >> [EC2("w1"), EC2("w2")]      # fan-out to list
```

Operator precedence matters: `-` (subtraction) binds more tightly than `>>` / `<<` (bitshift) in Python, so `A >> B - C` parses as `A >> (B - C)`. Wrap in parentheses when mixing: `(A >> B) - C`.

### Clusters

```python
from diagrams import Cluster

with Cluster("VPC"):
    with Cluster("Private Subnet"):
        svc = [ECS("svc1"), ECS("svc2")]
```

Unlimited nesting depth. Clusters accept `graph_attr` for styling (e.g. background colour).

### Edges

```python
from diagrams import Edge

node_a >> Edge(label="HTTPS", color="darkgreen", style="dashed") >> node_b
```

Attributes: `label` (text on the edge), `color` (X11 name or hex), `style` (solid | dashed | dotted | bold).

### Custom nodes

```python
from diagrams.custom import Custom

svc = Custom("My Service", "./icon.png")  # local PNG, ideally 256x256
```

## Key Techniques

- **Direction**: use `TB` for layered/hierarchical diagrams, `LR` for pipelines and flows
- **Transparent background**: `graph_attr={"bgcolor": "transparent"}`
- **Multiple outputs**: `outformat=["png", "svg"]`
- **Reduce edge noise**: import `Node` from `diagrams` and create blank junctions with `Node("", shape="plaintext", width="0", height="0")`, or merge overlapping edges with `graph_attr={"concentrate": "true", "splines": "spline"}`
- **Assign nodes to variables** when they connect to multiple other nodes
- **PEP 723** for standalone scripts so `uv run` handles the dependency automatically:
  ```python
  # /// script
  # dependencies = ["diagrams"]
  # ///
  ```

Overview

This skill helps you create, generate, and update architecture diagrams using the Python diagrams library (mingrammer/diagrams). It produces Python scripts that render to image files via Graphviz and reports the output path. Use it for cloud, infrastructure, network, Kubernetes, on-prem, and custom-node diagrams authored as code.

How this skill works

I inspect the requested architecture and produce a standalone Python script that uses diagrams, clusters, nodes, edges, and optional custom icons. I always set show=False, recommend Graphviz and diagrams checks, and choose sensible defaults for direction, output format, and styling. I provide runnable examples, file naming, and commands to execute the script and where the image will appear.

When to use it

  • When you ask to draw, generate, or update an architecture or infrastructure diagram
  • When code imports from diagrams, diagrams.aws, diagrams.gcp, diagrams.azure, diagrams.k8s, diagrams.onprem, or diagrams.custom
  • When you want diagrams as code for versioning, review, or CI generation
  • When you need exportable images (png, svg, pdf) from a programmatic diagram definition
  • When you want to mix provider nodes, clusters, and custom icons in one diagram

Best practices

  • Check prerequisites first: Graphviz (dot) and the diagrams package before running scripts
  • Always set show=False so scripts run non-interactively (CI, servers, terminals)
  • Assign frequently-referenced nodes to variables to avoid duplicated nodes and merge edges where appropriate
  • Use Cluster for subnets or logical groups and prefer TB for layered architectures, LR for pipelines
  • Prefer transparent background or multiple outformats when embedding diagrams into docs or slides

Example use cases

  • Generate an AWS service topology with ELB -> EC2 -> RDS and export both png and svg
  • Create a Kubernetes diagram showing Deployments, Pods, and Services with Cluster grouping for namespaces
  • Produce a network diagram combining on-premise firewalls, load balancers, and cloud connectors with custom icons
  • Convert a high-level system flow into a left-to-right pipeline diagram for onboarding docs
  • Automate diagram generation in CI to keep architecture visuals in sync with infrastructure changes

FAQ

What must I install before running a generated script?

Install Graphviz (dot) and the diagrams Python package. Verify dot is on PATH and pip install diagrams.

How do I run the script and find the output?

Run python3 <script>.py. The image file is written to the working directory; the Diagram name or filename param determines the file name and outformat controls extension(s).

diagrams-as-code skill by sammcj/agentic-coding