markdown-mermaid-writing
정보
이 스킬은 개발자가 마크다운에 Mermaid 다이어그램을 내장한 표준 형식으로 과학 문서와 보고서를 작성할 수 있도록 지원합니다. 포괄적인 스타일 가이드, 24가지 다이어그램 유형에 대한 참조 자료, 그리고 일관된 기술 문서 작성을 위한 9가지 문서 템플릿을 제공합니다. 분석 자료, 시각화 자료 또는 텍스트 기반 다이어그램이 필요한 모든 문서 작성 시 활용하세요.
빠른 설치
Claude Code
추천npx skills add K-Dense-AI/claude-scientific-skills -a claude-code/plugin add https://github.com/K-Dense-AI/claude-scientific-skillsgit clone https://github.com/K-Dense-AI/claude-scientific-skills.git ~/.claude/skills/markdown-mermaid-writingClaude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요
문서
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.
GitHub 저장소
연관 스킬
content-collections
메타이 스킬은 콘텐츠 콜렉션(Content Collections)을 위한 프로덕션 검증된 설정을 제공합니다. 콘텐츠 콜렉션은 Markdown/MDX 파일을 Zod 검증이 포함된 타입 안전한 데이터 콜렉션으로 변환해주는 TypeScript 최우선 도구입니다. 블로그, 문서 사이트 또는 콘텐츠 중심의 Vite + React 애플리케이션을 구축할 때 타입 안전성과 자동 콘텐츠 검증을 보장하기 위해 사용하세요. Vite 플러그인 구성과 MDX 컴파일부터 배포 최적화 및 스키마 검증에 이르기까지 모든 것을 다룹니다.
polymarket
메타이 스킬은 개발자들이 Polymarket 예측 시장 플랫폼을 활용한 애플리케이션을 구축할 수 있도록 지원하며, 거래 및 시장 데이터를 위한 API 통합 기능을 포함합니다. 또한 WebSocket을 통한 실시간 데이터 스트리밍을 제공하여 실시간 거래와 시장 활동을 모니터링할 수 있습니다. 이를 통해 거래 전략을 구현하거나 실시간 시장 업데이트를 처리하는 도구를 생성하는 데 활용할 수 있습니다.
creating-opencode-plugins
메타이 스킬은 개발자들이 명령어, 파일, LSP 작업 등 25개 이상의 이벤트 유형에 연결되는 OpenCode 플러그인을 만들 수 있도록 돕습니다. JavaScript/TypeScript 모듈을 위한 플러그인 구조, 이벤트 API 명세, 구현 패턴을 제공합니다. OpenCode AI 어시스턴트의 라이프사이클을 사용자 정의 이벤트 기반 로직으로 가로채거나, 모니터링하거나, 확장해야 할 때 사용하세요.
sglang
메타SGLang은 RadixAttention 프리픽스 캐싱을 활용하여 JSON, 정규식, 에이전트 워크플로우를 위한 고속 구조화 생성에 특화된 고성능 LLM 서빙 프레임워크입니다. 특히 반복되는 프리픽스가 있는 작업에서 상당히 빠른 추론 속도를 제공하여 복잡한 구조화 출력 및 다중 턴 대화에 이상적입니다. 제약 디코딩이 필요하거나 광범위한 프리픽스 공유가 있는 애플리케이션을 구축할 때는 vLLM과 같은 대안보다 SGLang을 선택하십시오.
