1Describe the audience, scope, required actors, and the decision the diagram should support.
2Choose the Mermaid diagram type before generating so the result matches the problem: flowchart, sequenceDiagram, classDiagram, or ER.
3Generate Mermaid code, then preview it immediately instead of copying AI output directly into documentation.
4Remove invented components, shorten labels, and split oversized results into smaller diagrams.
5Export SVG or PNG only after the source remains readable enough for future edits.

Common use cases

AI diagram draftingText to Mermaid conversionIncident timeline diagramsArchitecture review promptsProduct flow documentationMermaid syntax repair

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FAQ

Which AI provider is used?

The server calls DeepSeek directly and uses a local template fallback when DeepSeek is unavailable or not configured.

Are API keys exposed to the browser?

No. API keys are read only on the server through environment variables.

Can I generate a Mermaid sequence diagram from plain text?

Yes. Describe the actors and request order, choose sequenceDiagram, then review the generated Mermaid code before exporting it.

What should I include in a good text-to-Mermaid prompt?

Include the audience, diagram type, required actors or systems, important data stores, external services, and anything the model must not invent.

Should generated Mermaid be treated as final documentation?

No. Treat it as a draft. Preview the output, verify it against source material, and keep the Mermaid code editable in the final document.

Text to Mermaid turns plain-language requirements, incident notes, user journeys, and architecture descriptions into Mermaid diagrams for documentation.

It is useful when a developer has the flow in prose but needs editable Mermaid code for a README, design review, incident report, or product spec.

After generation, keep the Mermaid source editable, preview the SVG, and export only when labels, arrows, and diagram type match the story.

Demo: convert incident notes into Mermaid

Incident notes often contain actors, events, and timing in prose. Converting them into Mermaid can reveal missing steps, unclear ownership, and recovery actions that were buried in text.

Keep the input factual and chronological.
Ask for sequenceDiagram when order matters.
Ask for flowchart when the goal is decision or remediation logic.

At 10:05 the API started returning 503. The gateway retried twice, then the checkout service timed out while waiting for inventory. The worker queue kept accepting events. Recovery was to scale inventory pods and drain retries.

Editing pattern: choose the Mermaid diagram type first

A text-to-diagram result is stronger when the diagram type matches the question. Architecture notes, incidents, and product flows should not all become the same flowchart.

Use sequenceDiagram for request order and ownership.
Use flowchart for decision trees and user journeys.
Use ER diagrams for data relationships instead of forcing them into boxes and arrows.

Question: who called whom? -> sequenceDiagram
Question: what path can the user take? -> flowchart
Question: what data relates? -> erDiagram

Prompt template: generate a diagram reviewers can trust

The strongest prompts constrain the model. Instead of asking for a beautiful diagram, ask for a Mermaid source file that names the systems, keeps labels short, and avoids unverified services.

State the diagram audience and scope in the first sentence.
List required nodes and any nodes that must not appear.
Ask the model to keep edge labels short enough for a README or architecture decision record.

Create a Mermaid sequenceDiagram for backend reviewers. Scope: checkout payment authorization only. Required actors: Browser, Checkout API, Auth service, Payment provider, Order database. Do not add inventory or shipping. Keep message labels under 5 words.

Review checklist for Text to Mermaid

Use Text to Mermaid when you need to inspect source content visually before it becomes documentation, a pull request note, an incident write-up, or a handoff artifact. Convert product notes, incidents, and architecture text into Mermaid diagrams.

Before exporting, check that labels are readable, relationships match the source, generated examples do not contain private data, and the preview still makes sense after you edit the input.

Limits and troubleshooting

If the preview fails, reduce the input to the smallest complete example, confirm the format syntax, and then add sections back one at a time. Many rendering failures come from partial files, indentation mistakes, missing diagram headers, or copied snippets that depend on hidden context.

Treat the preview as a review surface rather than a source of truth. Generated diagrams, converted files, dashboards, and rule examples should be checked before they are used in production documentation or operations.

Example inputs to test

Requirements: Users paste diagram code, the app validates syntax, renders a preview, allows export, and suggests related tools.
Incident: A customer reports a broken export. Support checks logs, engineering reproduces, a fix is deployed, and support confirms resolution.
Architecture: Browser sends source text to a Next.js API route. The API calls DeepSeek, then returns Mermaid code for browser preview.

Tool maturity

AI beta

AI-assisted beta

This tool can generate editable source with an AI provider. Review the output, render it locally, and adjust details before publishing.

The maturity label is not a quality score. It tells visitors whether the tool is best for stable export, deeper debugging, quick parsing, or AI-assisted generation.