Architecture Diagram Prompt — Claude Skill

System diagrams
your team can
actually use.

Mermaid code. Architecture brief. Trade-offs. ADR stubs.

Describe your system and get working C4 or Sequence diagram code, a written brief, and decision records ready to commit.

Architecture Diagram Prompt is a Claude AI skill that generates Mermaid diagram code (C4, Sequence, Flowchart), a written architecture brief, trade-off notes, and ADR stubs — built for software architects and tech leads.

⚡ Replaces 3–5 hours of diagram drafting — runs in under 5 minutes.
Get this skill — $15
Output preview — Architecture Diagram Prompt
C4 Context · Mermaid
Stakeholder-level diagram — what the system is and who touches it.
```mermaid
C4Context
  title "Order Processing System — Context"
  Person(customer, "Customer", "Places and tracks orders")
  Person(ops, "Ops Team", "Manages fulfilment and disputes")
  System(ops_sys, "Order Processing System", "Handles order intake, routing, and status")
  System_Ext(payment, "Stripe", "Payment authorisation")
  System_Ext(wms, "Warehouse WMS", "Inventory and pick-pack")
  Rel(customer, ops_sys, "Places order", "HTTPS")
  Rel(ops_sys, payment, "Charges card", "REST/TLS")
  Rel(ops_sys, wms, "Sends pick list", "Webhook")
```
Renders natively in GitHub, GitLab, Notion, Confluence. Scope note included in the brief.
Architecture Brief · Component Rationale
Written narrative paired with every diagram.
What this diagram shows
C4 Context level — the system boundary and its external actors. Deliberately excludes internal services and databases; those belong in a Container diagram.

Key components
Order Processing System — central coordinator. Owns order state; delegates payment and fulfilment to external systems. Stateless horizontally scalable.

Stripe — external payment authority. Chosen over in-house processing to avoid PCI scope. Trade-off: dependency on third-party uptime SLA.
Every component gets a "why this, not that" rationale. No black boxes.
Sequence Diagram · Auth Flow
Critical path flows — async vs sync, auth handshakes.
```mermaid
sequenceDiagram
  actor C as Customer
  participant API as Order API
  participant Auth as Auth Service
  participant Pay as Stripe
  C->>API: POST /orders (JWT)
  API->>Auth: Verify token
  Auth-->>API: 200 OK + claims
  API->>Pay: Create payment intent
  Pay-->>API: client_secret
  API-->>C: 201 + client_secret
```
Auth boundaries and trust zones shown explicitly — not as an afterthought.
Trade-off Notes · ADR Stubs
Decision records your team can commit to the repo.
ADR-001: Stateless Order Service
Status: Proposed
Context: Order volume forecast 10× in 18 months. Team wants horizontal scale without sticky sessions.
Decision: Order service holds no session state. All state in PostgreSQL with row-level locking.
Consequences: Simpler scaling. Trade-off: DB becomes the bottleneck; mitigated by read replicas and connection pooling.

ADR-002: Stripe over in-house payments
Status: Accepted
Context: PCI DSS scope, 3-engineer team, 6-month runway.
ADR stubs use the Nygard format — ready to drop into /docs/decisions/.
Full output
What you receive
✓ Mermaid diagram code — C4 Context, Container, Sequence, or Flowchart
✓ Written architecture brief with component rationale
✓ Trade-off notes for every key decision
✓ ADR stubs (Nygard format) ready to commit
✓ Scope note — what the diagram shows and deliberately omits
✓ AI-native pattern support (LLM gateway, vector store, agent boundaries)
1 / 5
How it works

How does Architecture Diagram Prompt work?

  1. Tell Claude what you need — the skill asks 2-3 narrowing questions specific to the task.
  2. The skill runs live research and structures the output before writing a single word.
  3. An anti-slop quality gate checks the draft, then delivers a ready-to-use result for $15.
What you get

Why this diagram
gets committed.

🗺️
C4-model diagrams — right level for every audience, every time.
C4 · Mermaid · Sequence
📝
Written brief paired with every diagram — no more misread boxes.
Architecture brief
⚖️
Trade-off notes included — the "why" your team won't have to rediscover.
Decision rationale
📂
ADR stubs in Nygard format — drop into /docs/decisions and ship.
Repo-ready ADRs
Who it's for

Built for anyone
doing systems design.

✓
Software architects documenting systems for engineering teams.
✓
Tech leads who need diagrams before a sprint starts.
✓
Solutions architects scoping proposals for new clients.
✓
Senior engineers writing ADRs for a team without an architect.
Not what this is for
✕Business process or org-chart diagrams — this is software architecture only.
✕Pixel-perfect visual diagrams — output is Mermaid code for rendering in tools your team already uses.
✕Full design documents or RFCs — it produces briefs and ADR stubs, not complete spec docs.

The complete guide to architecture diagram prompts covers what makes diagrams that communicate decisions versus ones that just describe components.

"Dropped the Mermaid output straight into our GitHub wiki. First diagram we've had that the whole team actually reads. The ADR stubs saved us two hours of back-and-forth."
NB
Nikhil B.
Solutions architect · Bengaluru
Get it now
Diagrams
your team ships.
$15.

Instant download. Works with your free Claude account. 7-day refund if it's not what you expected.

Buy Architecture Diagram Skill — $15
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Quick answers

Do I need a paid Claude account for Architecture Diagram Prompt?

No. The free Claude plan is enough to get started and see the skill working. A Pro plan unlocks longer outputs.

How do I install the Architecture Diagram Prompt skill?

Download the .skill file, open Claude, go to Customize → Skills → Upload a skill, and drop the file in. It appears in your slash-command list immediately.

Can I edit or customise the output after I receive it?

Yes. The output is plain text you own and can edit freely. Most users tweak specific details or the call-to-action to fit their exact use case before sending or publishing.

How specific do my inputs need to be to get a good result?

The more specific your input, the more precise the output. The skill asks targeted questions to gather context — answering these in detail produces noticeably better results than generic one-line inputs.

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