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Markdown Mermaid Writing

K-DenseCommunityCreated by Clayton Young / Superior Byte Works, LLC (@borealBytes)Distributed by K-Dense

  • Skill
  • Tool integration
  • Documents and content
  • Apache-2.0
  • Low risk

From the author

Writes scientific Markdown documentation and Mermaid diagrams for workflows, relationships, timelines, and schemas. Provides syntax references, document templates, accessibility guidance, and version-aware rendering checks. Use when a user requests Markdown, Mermaid, or a text-based structural diagram; quantitative scientific figures require suitable plotting tools.
— the description by Clayton Young / Superior Byte Works, LLC (@borealBytes)

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to creating technical and scientific documentation using Markdown and Mermaid. It emphasizes the use of text-based diagrams for structural clarity, ensuring that workflows, architectures, and data models remain editable, version-controlled, and accessible. The skill includes templates for various document types and comprehensive guides for 23 different Mermaid diagram types, ensuring consistent formatting and adherence to accessibility standards.

What it does

  • Writes scientific Markdown reports, READMEs, and research documentation.
  • Creates structural Mermaid diagrams for workflows, timelines, schemas, and architectures.
  • Provides templates for common technical documents like ADRs, pull requests, and status reports.
  • Offers style guides for consistent Markdown formatting and Mermaid diagram design.
  • Includes accessibility guidance for diagrams using titles and descriptions.
  • Supports version-aware rendering checks for Mermaid diagrams.

When to use it

  • When you need to document complex workflows, system architectures, or data relationships.
  • When you want to maintain diagrams as editable text within a Git repository.
  • When creating technical reports that require a consistent, professional house style.
  • When you need to ensure your diagrams are accessible and renderable across different platforms.

Advantages

  • Diagrams are stored as plain text, making them easily diffable and version-controlled.
  • Reduces token usage compared to long-form text descriptions of relationships.
  • Promotes a consistent documentation style across projects.
  • Supports accessibility through standardized metadata.
  • Facilitates easy updates to diagrams without needing specialized image editing software.

Usage examples

“Create a Mermaid flowchart for a data processing pipeline.”
Generates a Markdown-formatted document containing a Mermaid flowchart block that maps the data pipeline steps, following the established style guide.
“Draft an Architecture Decision Record (ADR) for a new database choice.”
Produces a structured Markdown document using the ADR template, including placeholders for context, decision, and consequences.
“How do I create a sequence diagram for an API interaction?”
Provides the specific Mermaid sequence diagram syntax, a copy-paste template, and tips on how to style it according to the project's guidelines.
“Check if my Mermaid diagram is accessible.”
Reviews the diagram code for required accessibility metadata (accTitle/accDescr) and suggests improvements based on the Mermaid style guide.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/k-dense-ai/markdown-mermaid-writing/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip markdown-mermaid-writing.zip -d .agents/skills

Documentation by Clayton Young / Superior Byte Works, LLC (@borealBytes)

Markdown and Mermaid Writing

Overview

This skill provides an optional house style for Markdown documentation with Mermaid structural diagrams. Follow the requested output format, existing repository conventions, and journal requirements first. This skill does not replace scientific analysis or plotting.

A relationship expressed as Mermaid inside a .md file is editable text that diffs cleanly in git. A compatible host renders it without a separate user build step. It renders where the host has Mermaid support; plain Markdown viewers may show only code, and platforms/extensions ship different Mermaid versions. It uses a compact source representation, though token use depends on the diagram. Exporting SVG/PNG requires a renderer; retain the diagram source alongside exported figures.

"The more you get your reports and files in .md in just regular text, which mermaid is as well as being a simple 'script language'. This just helps with any downstream rendering and especially AI generated images (using mermaid instead of just long form text to describe relationships < tokens). Additionally mermaid can render along with markdown for easy use almost anywhere by humans or AI."

— Clayton Young (@borealBytes), K-Dense Discord, 2026-02-19

When to Use This Skill

Use this skill when:

  • Writing a requested Markdown report, README, methods overview, or research note

  • Diagramming a workflow, data pipeline, schema, state machine, or conceptual relationship

  • Maintaining editable Mermaid sources and their rendered SVG/PNG exports

Use scientific plotting tools directly for measured data, uncertainty, statistical graphics, exact geometry, or publication figures that Mermaid cannot faithfully represent. Mermaid is not a required precursor to a quantitative chart or an existing SVG/code-native asset.

🎨 The Source Format Philosophy

Why text-based diagrams win
What mattersMermaid in MarkdownPython / AI Image
Git diff readable✅ text sourcePlotting code/SVG can also be text
Editable source✅Plotting scripts and vector sources are editable
Compact relationship notationOftenDepends on representation
Native previewHost/version dependentViewer/format dependent
Parseable by AI without vision✅❌
Works in destinationCheck Mermaid support and versionCheck image format support
Accessible (screen readers)Check SVG metadata and text alternativeProvide alt text/data table
Convertible to image later✅ anytime— already image
The three-phase workflow
flowchart LR
    accTitle: Three-Phase Documentation Workflow
    accDescr: Markdown holds the structural diagram source. Quantitative charts come from data and plotting code; optional illustrations require a separate factual review.

    p1["📄 Phase 1<br/>Mermaid in Markdown<br/>(structural source)"]
    p2["🐍 Phase 2<br/>Python Generated<br/>(optional — data charts)"]
    p3["🎨 Phase 3<br/>AI Generated Visuals<br/>(optional — polish)"]
    out["📊 Final Deliverable"]

    p1 --> out
    data["Data and plotting code"] --> p2
    p1 -.->|"when needed"| p3
    p2 --> out
    p3 --> out

    classDef required fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#1e3a5f
    classDef optional fill:#fef9c3,stroke:#ca8a04,stroke-width:2px,color:#713f12
    classDef output fill:#dcfce7,stroke:#16a34a,stroke-width:2px,color:#14532d

    class p1 required
    class p2,p3 optional
    class out output

Retain Mermaid for structural diagrams and data/code for quantitative charts. An AI illustration is not a quantitative conversion; verify every label and relationship against its sources.

What Mermaid can express

This skill includes 23 diagram-type guides plus a composition guide. Mermaid supports additional types; these references are a curated subset, not an exhaustive version catalogue:

Use caseDiagram typeFile
Experimental workflow / decision logicFlowchartreferences/diagrams/flowchart.md
Service interactions / API calls / messagingSequencereferences/diagrams/sequence.md
Data model / schemaER diagramreferences/diagrams/er.md
State machine / lifecycleStatereferences/diagrams/state.md
Project timeline / roadmapGanttreferences/diagrams/gantt.md
Proportions / compositionPiereferences/diagrams/pie.md
System architecture (zoom levels)C4references/diagrams/c4.md
Concept hierarchy / brainstormMindmapreferences/diagrams/mindmap.md
Chronological events / historyTimelinereferences/diagrams/timeline.md
Class hierarchy / type relationshipsClassreferences/diagrams/class.md
User journey / satisfaction mapUser Journeyreferences/diagrams/user_journey.md
Two-axis comparison / prioritizationQuadrantreferences/diagrams/quadrant.md
Requirements traceabilityRequirementreferences/diagrams/requirement.md
Flow magnitude / resource distributionSankeyreferences/diagrams/sankey.md
Numeric trends / bar + line chartsXY Chartreferences/diagrams/xy_chart.md
Component layout / spatial arrangementBlockreferences/diagrams/block.md
Work item status / task columnsKanbanreferences/diagrams/kanban.md
Cloud infrastructure / service topologyArchitecturereferences/diagrams/architecture.md
Multi-dimensional comparison / skills radarRadarreferences/diagrams/radar.md
Hierarchical proportions / budgetTreemapreferences/diagrams/treemap.md
Binary protocol / data formatPacketreferences/diagrams/packet.md
Git branching / merge strategyGit Graphreferences/diagrams/git_graph.md
Code-style sequence (programming syntax)ZenUMLreferences/diagrams/zenuml.md
Multi-diagram composition patternsComplex Examplesreferences/diagrams/complex_examples.md

💡 Pick the right type, not the easy one. Don't default to flowcharts for everything. A timeline beats a flowchart for chronological events. A sequence beats a flowchart for service interactions. Scan the table and match.


🔧 Core workflow

Step 1: Identify the document type

Check if a template exists before writing from scratch:

Document typeTemplate
Pull request recordtemplates/pull_request.md
Issue / bug / feature requesttemplates/issue.md
Sprint / project boardtemplates/kanban.md
Architecture decision (ADR)templates/decision_record.md
Presentation / briefingtemplates/presentation.md
Research paper / analysistemplates/research_paper.md
Project documentationtemplates/project_documentation.md
How-to / tutorialtemplates/how_to_guide.md
Status reporttemplates/status_report.md
Step 2: Read the style guide

For this Markdown workflow, read references/markdown_style_guide.md. Treat emoji, heading counts, and horizontal rules as house style rather than Markdown syntax requirements.

Key rules to internalize:

  • One H1 per document — the title. Never more.

  • Emoji on H2 headings only — one emoji per H2, none in H3/H4

  • Support factual claims — use verified sources and the requested citation format

  • Bold sparingly — max 2-3 bold terms per paragraph, never full sentences

  • Optional horizontal rules after </details> when they improve separation

  • Tables over prose for comparisons, configurations, structured data

  • Diagrams over walls of text — if it describes flow, structure, or relationships, add Mermaid

Step 3: Pick the diagram type and read its guide

Before creating any Mermaid diagram: read references/mermaid_style_guide.md.

Then open the specific type file (e.g., references/diagrams/flowchart.md) for the exemplar, tips, and copy-paste template.

Add accessibility metadata for types that emit it in the chosen renderer:

accTitle: Short Name 3-8 Words
accDescr: One or two sentences explaining what this diagram shows.
  • Prefer host themes; %%{init} directives are deprecated in favor of YAML configuration

  • Prefer reusable classDef where supported; style syntax is diagram-specific

  • One emoji per node max — at the start of the label

  • Use descriptive IDs with the type's syntax: snake_case works for flowcharts; ER/class/state conventions differ

Step 4: Write the document

Start from the template. Apply the markdown style guide. Place diagrams inline with related text — not in a separate "Figures" section.

Render in the actual destination before delivery. Check its Mermaid version and plugin requirements before choosing newer diagram types; GitHub documents an info diagram for this check. A successful latest-version local preview does not establish GitHub or another host will render it. Where Mermaid is unsupported, supply a rendered SVG/PNG with a text description alongside the retained .md source.

Step 5: Retain source and verification

Keep the .md source, rendered deliverable, and tested renderer version together. Follow the project's version-control workflow; this skill does not itself authorize a commit or publication. For CLI export, embedding, and the tested accessibility matrix, read Current rendering and validation.


⚠️ Common pitfalls

Radar chart syntax (radar-beta)

WRONG (shown as text so it does not break the document renderer):

radar
title Example
x-axis ["A", "B", "C"]
"Series" : [1, 2, 3]

CORRECT:

radar-beta
accTitle: Example Radar Scores
accDescr: Illustrative values of one, two, and three on a shared zero-to-three scale.
title Example
axis a["A"], b["B"], c["C"]
curve series["Series"]{1, 2, 3}
max 3
  • Use radar-beta not radar (the bare keyword doesn't exist)

  • Use axis to define dimensions, not x-axis

  • Use curve to define data series, not quoted labels with colon

  • Mermaid 12.0.0 radar emits accTitle/accDescr; check older hosts and retain a visible description

XY Chart vs Radar confusion
DiagramKeywordAxis syntaxData syntax
XY Chart (bars/lines)xychart-betax-axis ["Label1", "Label2"]bar [10, 20] or line [10, 20]
Radar (spider/web)radar-betaaxis id["Label"]curve id["Label"]{10, 20}
Forgetting accTitle/accDescr on supported types

Only some diagram types support accTitle/accDescr. For those that don't, always place a descriptive italic paragraph directly above the code block:

Radar chart comparing three methods on a stated, common score scale. See the data table for exact values.

radar-beta
...

🔗 Integration with other skills

With scientific-schematics

scientific-schematics generates AI-powered publication-quality images (PNG). Use the Mermaid diagram as the brief for the schematic:

Workflow:
1. Create the concept as Mermaid in .md (this skill — Phase 1)
2. Describe the same concept to scientific-schematics for a polished PNG (Phase 3)
3. Commit both — the .md as source, the PNG as a supplementary figure
With scientific-writing

For a manuscript that uses Mermaid structural figures, this skill handles diagram syntax. Follow the manuscript's required figure formats and scientific visualization conventions.

Workflow:
1. Use scientific-writing to draft the manuscript
2. For every figure that shows a workflow, architecture, or relationship:
   - Replace placeholder with a Mermaid diagram following this skill's guide
3. Use plotting or schematic tools where appropriate to the scientific content
With literature-review

Literature review produces summaries with lots of relationship data. Use this skill to:

  • Create concept maps (Mindmap) of the literature landscape

  • Show publication timelines (Timeline or Gantt)

  • Compare methodologies (Quadrant or Radar)

  • Diagram data flows described in papers (Sequence or Flowchart)

With any skill that produces output documents

Before finalizing a document using this skill, check:

  • [ ] Does the document use a template? If so, did I start from the right one?

  • [ ] Is each diagram in an appropriate format, with working accessibility metadata or a text alternative?

  • [ ] Is configuration supported by the destination and tested in light/dark themes?

  • [ ] Do citations support external claims, and are synthetic values labeled?

  • [ ] One H1, emoji on H2 only?

  • [ ] Does the final Markdown/HTML structure render correctly?


📚 Reference index

Style guides
GuidePathLinesWhat it covers
Markdown Style Guidereferences/markdown_style_guide.mdsee fileHeadings, formatting, citations, tables, Mermaid integration, templates, quality checklist
Mermaid Style Guidereferences/mermaid_style_guide.mdsee fileAccessibility, emoji set, color classes, theme neutrality, type selection, complexity tiers
Current Renderingreferences/current-rendering.mdsee fileMermaid 12 changes, CLI export, browser APIs, tested accessibility matrix, scientific checks
Diagram guides (23 types plus composition)

Each file contains: production-quality exemplar, tips specific to that type, and a copy-paste template.

references/diagrams/ — architecture, block, c4, class, complex_examples, er, flowchart, gantt, git_graph, kanban, mindmap, packet, pie, quadrant, radar, requirement, sankey, sequence, state, timeline, treemap, user_journey, xy_chart, zenuml

Document templates (9 types)

templates/ — decision_record, how_to_guide, issue, kanban, presentation, project_documentation, pull_request, research_paper, status_report

Examples

assets/examples/example-research-report.md — a synthetic quality-control report with explicitly invented data, an auditable count table, a structural flowchart, a bar chart, and a chronology. It makes no experimental or software API claims.


📝 Attribution

All style guides, diagram type guides, and document templates in this skill are ported from the SuperiorByteWorks-LLC/agent-project repository under the Apache-2.0 License.

This skill (as part of scientific-agent-skills) is distributed under the MIT License. The included Apache-2.0 content is compatible for downstream use with attribution retained, as preserved in the file headers throughout this skill.


[^1]: GitHub Blog. (2022). "Include diagrams in your Markdown files with Mermaid." https://github.blog/2022-02-14-include-diagrams-markdown-files-mermaid/

[^2]: Mermaid. "Mermaid Diagramming and Charting Tool." https://mermaid.js.org/

Files

references/diagrams/complex_examples.md

<!-- Source: https://github.com/SuperiorByteWorks-LLC/agent-project | License: Apache-2.0 | Author: Clayton Young / Superior Byte Works, LLC (Boreal Bytes) -->

Composing Complex Diagram Sets

Back to Style Guide — This file covers how to combine multiple diagram types to document complex systems comprehensively.

Purpose: A single diagram captures a single perspective. Real documentation often needs multiple diagram types working together — an overview flowchart linked to a detailed sequence diagram, an ER schema paired with a state machine showing entity lifecycle, a Gantt timeline complemented by architecture before/after views. This file teaches you when and how to compose diagrams for maximum clarity.


When to Compose Multiple Diagrams

What you're documentingDiagram combinationWhy it works
Full system architectureC4 Context + Architecture + Sequence (key flows)Context for stakeholders, infrastructure for ops, sequences for developers
API design documentationER (data model) + Sequence (request flows) + State (entity lifecycle)Schema for the database team, interactions for backend, states for business logic
Feature specificationFlowchart (happy path) + Sequence (service interactions) + User Journey (UX)Process for PM, implementation for engineers, experience for design
Migration projectGantt (timeline) + Architecture (before/after) + Flowchart (migration process)Schedule for leadership, topology for infra, steps for the migration team
Onboarding documentationUser Journey + Flowchart (setup steps) + Sequence (first API call)Experience map for product, checklist for new hires, technical walkthrough for devs
Incident responseState (alert lifecycle) + Sequence (escalation flow) + Flowchart (decision tree)Status tracking for on-call, communication for management, triage for responders

Pattern 1: Overview + Detail

When to use: You need both the big picture AND the specifics. Leadership sees the overview; engineers drill into the detail.

The overview diagram shows high-level phases or components. One or more detail diagrams zoom into specific phases showing the internal interactions.

Overview — Release Pipeline
flowchart LR
    accTitle: Release Pipeline Overview
    accDescr: High-level four-phase release pipeline from code commit through build, staging, and production deployment

    subgraph source ["📥 Source"]
        commit[📝 Code commit] --> pr_review[🔍 PR review]
    end

    subgraph build ["🔧 Build"]
        compile[⚙️ Compile] --> test[🧪 Test suite]
        test --> scan[🔐 Security scan]
    end

    subgraph staging ["🚀 Staging"]
        deploy_stg[☁️ Deploy staging] --> smoke[🧪 Smoke tests]
        smoke --> approval{👤 Approved?}
    end

    subgraph production ["✅ Production"]
        canary[🚀 Canary 5%] --> rollout[🚀 Full rollout]
        rollout --> monitor[📊 Monitor metrics]
    end

    source --> build
    build --> staging
    approval -->|Yes| production
    approval -->|No| source

    classDef phase_start fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#1e3a5f
    classDef phase_test fill:#fef9c3,stroke:#ca8a04,stroke-width:2px,color:#713f12
    classDef phase_deploy fill:#dcfce7,stroke:#16a34a,stroke-width:2px,color:#14532d

    class commit,pr_review,compile phase_start
    class test,scan,smoke,approval phase_test
    class deploy_stg,canary,rollout,monitor phase_deploy

The production deployment phase involves multiple service interactions. See the detail sequence below for the canary rollout process.

Detail — Canary Deployment Sequence
sequenceDiagram
    accTitle: Canary Deployment Service Interactions
    accDescr: Detailed sequence showing how the CI server orchestrates a canary deployment through the container registry, Kubernetes cluster, and monitoring stack with automated rollback on failure

    participant ci as ⚙️ CI Server
    participant registry as 📦 Container Registry
    participant k8s as ☁️ Kubernetes
    participant monitor as 📊 Monitoring
    participant oncall as 👤 On-Call Engineer

    ci->>registry: 📤 Push tagged image
    registry-->>ci: ✅ Image stored

    ci->>k8s: 🚀 Deploy canary (5% traffic)
    k8s-->>ci: ✅ Canary pods running

    ci->>monitor: 📊 Start canary analysis
    Note over monitor: ⏰ Observe for 15 minutes

    loop 📊 Every 60 seconds
        monitor->>k8s: 🔍 Query error rate
        k8s-->>monitor: 📊 Metrics response
    end

    alt ✅ Error rate below threshold
        monitor-->>ci: ✅ Canary healthy
        ci->>k8s: 🚀 Promote to 100%
        k8s-->>ci: ✅ Full rollout complete
        ci->>monitor: 📊 Continue monitoring
    else ❌ Error rate above threshold
        monitor-->>ci: ❌ Canary failing
        ci->>k8s: 🔄 Rollback to previous
        k8s-->>ci: ✅ Rollback complete
        ci->>oncall: ⚠️ Alert: canary failed
        Note over oncall: 📋 Investigate root cause
    end
How these connect
  • The overview flowchart shows the full pipeline with subgraph-to-subgraph connections — leadership reads this to understand the release process

  • The detail sequence zooms into "Canary 5% → Full rollout" from the Production subgraph, showing the actual service interactions an engineer would debug

  • Naming is consistent — "Canary" and "Monitor metrics" appear in both diagrams, creating a clear bridge between overview and detail


Pattern 2: Multi-Perspective Documentation

When to use: The same system needs to be documented for different audiences — database teams, backend engineers, and product managers each need a different view of the same feature.

This example documents a User Authentication feature from three perspectives.

Data Model — for database team
erDiagram
    accTitle: Authentication Data Model
    accDescr: Five-entity schema for user authentication covering users, sessions, refresh tokens, login attempts, and MFA devices with cardinality relationships

    USER ||..o{ SESSION : "has"
    USER ||..o{ REFRESH_TOKEN : "owns"
    USER ||..o{ LOGIN_ATTEMPT : "produces"
    USER ||..o{ MFA_DEVICE : "registers"
    SESSION ||..|| REFRESH_TOKEN : "paired with"

    USER {
        uuid id PK "🔑 Primary key"
        string email "📧 Unique login"
        string password_hash "🔐 Bcrypt hash"
        boolean mfa_enabled "🔒 MFA flag"
        timestamp last_login "⏰ Last active"
    }

    SESSION {
        uuid id PK "🔑 Primary key"
        uuid user_id FK "👤 Session owner"
        string ip_address "🌐 Client IP"
        string user_agent "📋 Browser info"
        timestamp expires_at "⏰ Expiration"
    }

    REFRESH_TOKEN {
        uuid id PK "🔑 Primary key"
        uuid user_id FK "👤 Token owner"
        uuid session_id FK "🔗 Paired session"
        string token_hash "🔐 Hashed token"
        boolean revoked "❌ Revoked flag"
        timestamp expires_at "⏰ Expiration"
    }

    LOGIN_ATTEMPT {
        uuid id PK "🔑 Primary key"
        uuid user_id FK "👤 Attempting user"
        string ip_address "🌐 Source IP"
        boolean success "✅ Outcome"
        string failure_reason "⚠️ Why failed"
        timestamp attempted_at "⏰ Attempt time"
    }

    MFA_DEVICE {
        uuid id PK "🔑 Primary key"
        uuid user_id FK "👤 Device owner"
        string device_type "📱 TOTP or WebAuthn"
        string credential_reference "🔐 Credential storage reference"
        boolean verified "✅ Setup complete"
        timestamp registered_at "⏰ Registered"
    }
Authentication Flow — for backend team
sequenceDiagram
    accTitle: Login Flow with MFA
    accDescr: Step-by-step authentication sequence showing credential validation, conditional MFA challenge, token issuance, and failure handling between browser, API, auth service, and database

    participant B as 👤 Browser
    participant API as 🌐 API Gateway
    participant Auth as 🔐 Auth Service
    participant DB as 💾 Database

    B->>API: 📤 POST /login (email, password)
    API->>Auth: 🔐 Validate credentials
    Auth->>DB: 🔍 Fetch user by email
    DB-->>Auth: 👤 User record

    Auth->>Auth: 🔐 Verify password hash

    alt ❌ Invalid password
        Auth->>DB: 📝 Log failed attempt
        Auth-->>API: ❌ 401 Unauthorized
        API-->>B: ❌ Invalid credentials
    else ✅ Password valid
        alt 🔒 MFA enabled
            Auth-->>API: ⚠️ 202 MFA required
            API-->>B: 📱 Show MFA prompt

            B->>API: 📤 POST /login/mfa (code)
            API->>Auth: 🔐 Verify MFA code
            Auth->>DB: 🔍 Fetch MFA device
            DB-->>Auth: 📱 Device record
            Auth->>Auth: 🔐 Validate TOTP

            alt ❌ Invalid code
                Auth-->>API: ❌ 401 Invalid code
                API-->>B: ❌ Try again
            else ✅ Code valid
                Auth->>DB: 📝 Create session + tokens
                Auth-->>API: ✅ 200 + tokens
                API-->>B: ✅ Set cookies + redirect
            end
        else 🔓 No MFA
            Auth->>DB: 📝 Create session + tokens
            Auth-->>API: ✅ 200 + tokens
            API-->>B: ✅ Set cookies + redirect
        end
    end
Login Experience — for product team
journey
    accTitle: Login Experience Journey Map
    accDescr: User satisfaction scores across the sign-in experience for password-only users and MFA users showing friction points in the multi-factor flow

    title 👤 Login Experience
    section 🔐 Sign In
        Navigate to login          : 4 : User
        Enter email and password   : 3 : User
        Click sign in button       : 4 : User
    section 📱 MFA Challenge
        Receive MFA prompt         : 3 : MFA User
        Open authenticator app     : 2 : MFA User
        Enter 6-digit code         : 2 : MFA User
        Handle expired code        : 1 : MFA User
    section ✅ Post-Login
        Land on dashboard          : 5 : User
        See personalized content   : 5 : User
        Resume previous session    : 4 : User
How these connect
  • Same entities, different views — "User", "Session", "MFA Device" appear in the ER diagram as tables, in the sequence as participants/operations, and in the journey as experience touchpoints

  • Each audience gets actionable information — the DB team sees candidate fields and cardinality, the backend team sees illustrative request/error flows, and the product team sees hypothetical experience scores; these are not verified implementations or measurements

  • The journey reveals what the sequence hides — the sequence diagram shows MFA as a clean conditional branch, but the invented low scores indicate where a real study might look for friction. Gather evidence before making a product decision


Pattern 3: Before/After Architecture

When to use: Migration documentation where stakeholders need to see the current state, the target state, and understand the transformation.

Current State — Monolith
flowchart TB
    accTitle: Current State Monolith Architecture
    accDescr: Single Rails monolith handling all traffic through one server connected to one database showing the scaling bottleneck

    client([👤 All traffic]) --> mono[🖥️ Rails Monolith]
    mono --> db[(💾 Single PostgreSQL)]
    mono --> jobs[⏰ Background jobs]
    jobs --> db

    classDef bottleneck fill:#fee2e2,stroke:#dc2626,stroke-width:2px,color:#7f1d1d
    classDef neutral fill:#f3f4f6,stroke:#6b7280,stroke-width:2px,color:#1f2937

    class mono,db bottleneck
    class client,jobs neutral

⚠️ Illustrative assumption: This deployment has a shared database bottleneck and restarts on deployment. These are properties to measure, not inherent facts about monoliths.

Target State — Microservices
flowchart TB
    accTitle: Target State Microservices Architecture
    accDescr: Decomposed microservices architecture with API gateway routing to independent services each with their own data store and a shared message queue for async communication

    client([👤 All traffic]) --> gw[🌐 API Gateway]

    subgraph services ["⚙️ Services"]
        user_svc[👤 User Service]
        order_svc[📋 Order Service]
        product_svc[📦 Product Service]
    end

    subgraph data ["💾 Data Stores"]
        user_db[(💾 Users DB)]
        order_db[(💾 Orders DB)]
        product_db[(💾 Products DB)]
    end

    gw --> user_svc
    gw --> order_svc
    gw --> product_svc

    user_svc --> user_db
    order_svc --> order_db
    product_svc --> product_db

    order_svc --> mq[📥 Message Queue]
    mq --> user_svc
    mq --> product_svc

    classDef gateway fill:#ede9fe,stroke:#7c3aed,stroke-width:2px,color:#3b0764
    classDef service fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#1e3a5f
    classDef datastore fill:#dcfce7,stroke:#16a34a,stroke-width:2px,color:#14532d
    classDef infra fill:#fef9c3,stroke:#ca8a04,stroke-width:2px,color:#713f12

    class gw gateway
    class user_svc,order_svc,product_svc service
    class user_db,order_db,product_db datastore
    class mq infra

✅ Proposed outcome: Independent services and data stores may reduce the measured shared bottleneck. Verify scaling, consistency, operational cost, and failure recovery before claiming improvement.

How these connect
  • Same layout, different complexity — both diagrams use flowchart TB so the structural transformation is visually obvious. The monolith is 4 nodes; the target is 11 nodes with subgraphs.

  • Color tells the story — the monolith uses red (danger) on the bottleneck components. The target uses blue/green/purple to show healthy, differentiated components.

  • Prose bridges the diagrams — the ⚠️ problem callout and ✅ result callout explain why the architecture changes, not just what changed.


Linking Diagrams in Documentation

When composing diagrams in a real document, follow these practices:

PracticeExample
Use headers as anchorsSee [Authentication Flow](#authentication-flow-for-backend-team) for the full login sequence
Reference specific nodes"The API Gateway from the overview connects to the services detailed below"
Consistent namingSame entity = same name in every diagram (User Service, not "User Svc" in one and "Users API" in another)
Adjacent placementKeep related diagrams in consecutive sections, not scattered across the document
Bridging proseOne sentence between diagrams explaining how they connect: "The sequence below zooms into the Deploy phase from the pipeline above"
Audience labelsMark sections: "### Data Model — for database team" so readers skip to their view

Choosing Your Composition Strategy

flowchart TB
    accTitle: Diagram Composition Decision Tree
    accDescr: Decision flowchart for choosing between single diagram, overview plus detail, multi-perspective, or before-after composition strategies based on audience and documentation needs

    start([📋 What are you documenting?]) --> audience{👥 Multiple audiences?}

    audience -->|Yes| perspectives[📐 Multi-Perspective]
    audience -->|No| depth{📏 Need both summary and detail?}

    depth -->|Yes| overview[🔍 Overview + Detail]
    depth -->|No| change{🔄 Showing a change over time?}

    change -->|Yes| before_after[⚡ Before / After]
    change -->|No| single[📊 Single diagram is fine]

    classDef decision fill:#fef9c3,stroke:#ca8a04,stroke-width:2px,color:#713f12
    classDef result fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#1e3a5f
    classDef start_style fill:#ede9fe,stroke:#7c3aed,stroke-width:2px,color:#3b0764

    class audience,depth,change decision
    class perspectives,overview,before_after,single result
    class start start_style

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Needs Node.js

The author says: Markdown authoring needs no runtime. Local rendering targets Mermaid and Mermaid CLI 12.0.0, Node.js 22.13+ and a supported Chromium browser. Package or CDN installation needs network access; no credentials required.

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Clayton Young / Superior Byte Works, LLC (@borealBytes)
Publisher
K-Dense (Community)
Distributed by
K-Dense
Source
K-Dense-AI/scientific-agent-skills · skills/markdown-mermaid-writing · commit a25cf9e
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (written by AutoGineer)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Clayton Young / Superior Byte Works, LLC (@borealBytes) or K-Dense.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download markdown-mermaid-writing.zip