markdown-mermaid-writing▌
K-Dense-AI/scientific-agent-skills · updated Jun 4, 2026
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### Markdown Mermaid Writing
- ›name: "markdown-mermaid-writing"
- ›description: "Comprehensive markdown and Mermaid diagram writing skill. Use when creating any scientific document, report, analysis, or visualization. Establishes text-based diagrams as the default documentation st..."
- ›allowed-tools: "Read Write Edit Bash"
| name | markdown-mermaid-writing |
| description | Comprehensive markdown and Mermaid diagram writing skill. Use when creating any scientific document, report, analysis, or visualization. Establishes text-based diagrams as the default documentation standard with full style guides (markdown + mermaid), 24 diagram type references, and 9 document templates. |
| allowed-tools | Read Write Edit Bash |
| license | Apache-2.0 |
| metadata | version: "1.1" skill-author: Clayton Young / Superior Byte Works, LLC (@borealBytes) skill-source: https://github.com/SuperiorByteWorks-LLC/agent-project skill-version: "1.0.0" skill-contributors: "Clayton Young (Superior Byte Works, LLC / @borealBytes; Author and originator); K-Dense Team (K-Dense Inc.; Integration target and community feedback)" |
Markdown and Mermaid Writing
Overview
This skill teaches you — and enforces a standard for — creating scientific documentation using markdown with embedded Mermaid diagrams as the default and canonical format.
The core bet: a relationship expressed as a Mermaid diagram inside a .md file is more
valuable than any image. It is text, so it diffs cleanly in git. It requires no build step.
It renders natively on GitHub, GitLab, Notion, VS Code, and any markdown viewer. It uses
fewer tokens than a prose description of the same relationship. And it can always be
converted to a polished image later — but the text version remains the source of truth.
"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:
- Creating any scientific document — reports, analyses, manuscripts, methods sections
- Writing any documentation — READMEs, how-tos, decision records, project docs
- Producing any diagram — workflows, data pipelines, architectures, timelines, relationships
- Generating any output that will be version-controlled — if it's going into git, it should be markdown
- Working with any other skill — this skill defines the documentation layer that wraps every other output
- Someone asks you to "add a diagram" or "visualize the relationship" — Mermaid first, always
Do NOT start with Python matplotlib, seaborn, or AI image generation for structural or relational diagrams. Those are Phase 2 and Phase 3 — only used when Mermaid cannot express what's needed (e.g., scatter plots with real data, photorealistic images).
🎨 The Source Format Philosophy
Why text-based diagrams win
| What matters | Mermaid in Markdown | Python / AI Image |
|---|---|---|
| Git diff readable | ✅ | ❌ binary blob |
| Editable without regenerating | ✅ | ❌ |
| Token efficient vs. prose | ✅ smaller | ❌ larger |
| Renders without a build step | ✅ | ❌ needs hosting |
| Parseable by AI without vision | ✅ | ❌ |
| Works in GitHub / GitLab / Notion | ✅ | ⚠️ if hosted |
| Accessible (screen readers) | ✅ accTitle/accDescr | ⚠️ needs alt text |
| Convertible to image later | ✅ anytime | — already image |
The three-phase workflow
flowchart LR
accTitle: Three-Phase Documentation Workflow
accDescr: Phase 1 Mermaid in markdown is always required and is the source of truth. Phases 2 and 3 are optional downstream conversions for polished output.
p1["📄 Phase 1<br/>Mermaid in Markdown<br/>(ALWAYS — source of truth)"]
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
p1 -.->|"when needed"| 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
Phase 1 is mandatory. Even if you proceed to Phase 2 or 3, the Mermaid source stays committed.
What Mermaid can express
Mermaid covers 24 diagram types. Almost every scientific relationship fits one:
| Use case | Diagram type | File |
|---|---|---|
| Experimental workflow / decision logic | Flowchart | references/diagrams/flowchart.md |
| Service interactions / API calls / messaging | Sequence | references/diagrams/sequence.md |
| Data model / schema | ER diagram | references/diagrams/er.md |
| State machine / lifecycle | State | references/diagrams/state.md |
| Project timeline / roadmap | Gantt | references/diagrams/gantt.md |
| Proportions / composition | Pie | references/diagrams/pie.md |
| System architecture (zoom levels) | C4 | references/diagrams/c4.md |
| Concept hierarchy / brainstorm | Mindmap | references/diagrams/mindmap.md |
| Chronological events / history | Timeline | references/diagrams/timeline.md |
| Class hierarchy / type relationships | Class | references/diagrams/class.md |
| User journey / satisfaction map | User Journey | references/diagrams/user_journey.md |
| Two-axis comparison / prioritization | Quadrant | references/diagrams/quadrant.md |
| Requirements traceability | Requirement | references/diagrams/requirement.md |
| Flow magnitude / resource distribution | Sankey | references/diagrams/sankey.md |
| Numeric trends / bar + line charts | XY Chart | references/diagrams/xy_chart.md |
| Component layout / spatial arrangement | Block | references/diagrams/block.md |
| Work item status / task columns | Kanban | references/diagrams/kanban.md |
| Cloud infrastructure / service topology | Architecture | references/diagrams/architecture.md |
| Multi-dimensional comparison / skills radar | Radar | references/diagrams/radar.md |
| Hierarchical proportions / budget | Treemap | references/diagrams/treemap.md |
| Binary protocol / data format | Packet | references/diagrams/packet.md |
| Git branching / merge strategy | Git Graph | references/diagrams/git_graph.md |
| Code-style sequence (programming syntax) | ZenUML | references/diagrams/zenuml.md |
| Multi-diagram composition patterns | Complex Examples | references/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 type | Template |
|---|---|
| Pull request record | templates/pull_request.md |
| Issue / bug / feature request | templates/issue.md |
| Sprint / project board | templates/kanban.md |
| Architecture decision (ADR) | templates/decision_record.md |
| Presentation / briefing | templates/presentation.md |
| Research paper / analysis | templates/research_paper.md |
| Project documentation | templates/project_documentation.md |
| How-to / tutorial | templates/how_to_guide.md |
| Status report | templates/status_report.md |
Step 2: Read the style guide
Before writing any .md file: read references/markdown_style_guide.md.
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
- Cite everything — every external claim gets a footnote
[^N]with full URL - Bold sparingly — max 2-3 bold terms per paragraph, never full sentences
- Horizontal rule after every
</details>— mandatory - 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.
Mandatory rules for every diagram:
accTitle: Short Name 3-8 Words
accDescr: One or two sentences explaining what this diagram shows.
- No
%%{init}directives — breaks GitHub dark mode - No inline
style— useclassDefonly - One emoji per node max — at the start of the label
snake_casenode IDs — match the label
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.
Step 5: Commit as text
The .md file with embedded Mermaid is what gets committed. If you also generated a PNG or AI image, those are supplementary — the markdown is the source.
⚠️ Common pitfalls
Radar chart syntax (radar-beta)
WRONG:
radar
title Example
x-axis ["A", "B", "C"]
"Series" : [1, 2, 3]
CORRECT:
radar-beta
title Example
axis a["A"], b["B"], c["C"]
curve series["Series"]{1, 2, 3}
max 3
- Use
radar-betanotradar(the bare keyword doesn't exist) - Use
axisto define dimensions, notx-axis - Use
curveto define data series, not quoted labels with colon - No
accTitle/accDescr— radar-beta doesn't support accessibility annotations; always add a descriptive italic paragraph above the diagram
XY Chart vs Radar confusion
| Diagram | Keyword | Axis syntax | Data syntax |
|---|---|---|---|
| XY Chart (bars/lines) | xychart-beta | x-axis ["Label1", "Label2"] | bar [10, 20] or line [10, 20] |
| Radar (spider/web) | radar-beta | axis 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 across five performance dimensions. Note: Radar charts do not support accTitle/accDescr.
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
When scientific-writing produces a manuscript, all diagrams and structural figures should use this skill's standards. The writing skill handles prose and citations; this skill handles visual structure.
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 scientific-schematics only for figures that truly need photorealistic/complex rendering
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 any document from any skill, apply this skill's checklist:
- Does the document use a template? If so, did I start from the right one?
- Are all diagrams in Mermaid with
accTitle+accDescr? - No
%%{init}, no inlinestyle, onlyclassDef? - Are all external claims cited with
[^N]? - One H1, emoji on H2 only?
- Horizontal rules after every
</details>?
📚 Reference index
Style guides
| Guide | Path | Lines | What it covers |
|---|---|---|---|
| Markdown Style Guide | references/markdown_style_guide.md | ~733 | Headings, formatting, citations, tables, Mermaid integration, templates, quality checklist |
| Mermaid Style Guide | references/mermaid_style_guide.md | ~458 | Accessibility, emoji set, color classes, theme neutrality, type selection, complexity tiers |
Diagram type guides (24 types)
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 complete scientific research report demonstrating proper heading hierarchy, multiple diagram types (flowchart, sequence, gantt), tables, footnote citations, collapsible sections, and all style guide rules applied.
📝 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.
- Source: https://github.com/SuperiorByteWorks-LLC/agent-project
- Author: Clayton Young / Superior Byte Works, LLC (@borealBytes)
- License: Apache-2.0
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.
How to use markdown-mermaid-writing on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add markdown-mermaid-writing
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches markdown-mermaid-writing from GitHub repository K-Dense-AI/scientific-agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate markdown-mermaid-writing. Access the skill through slash commands (e.g., /markdown-mermaid-writing) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★54 reviews- ★★★★★Fatima Nasser· Dec 28, 2024
Useful defaults in markdown-mermaid-writing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Arjun Reddy· Dec 24, 2024
We added markdown-mermaid-writing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Arjun Kim· Dec 16, 2024
markdown-mermaid-writing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Dhruvi Jain· Dec 8, 2024
markdown-mermaid-writing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Oshnikdeep· Nov 27, 2024
markdown-mermaid-writing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ira Nasser· Nov 19, 2024
markdown-mermaid-writing has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ira Farah· Nov 15, 2024
Keeps context tight: markdown-mermaid-writing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Hana Mehta· Nov 7, 2024
markdown-mermaid-writing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Arjun White· Oct 26, 2024
We added markdown-mermaid-writing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ganesh Mohane· Oct 18, 2024
Keeps context tight: markdown-mermaid-writing is the kind of skill you can hand to a new teammate without a long onboarding doc.
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