MCPInstall

markdown-mermaid-writing

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.

Installs
2.1K
Last 24h
+14
Trending rank
#7257
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill markdown-mermaid-writing
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads markdown-mermaid-writing automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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.


FAQ

What does the markdown-mermaid-writing skill do?

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.

How do I install markdown-mermaid-writing?

Run npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill markdown-mermaid-writing in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/markdown-mermaid-writing/ (personal) or .claude/skills/markdown-mermaid-writing/ (project).

Which AI agents can use markdown-mermaid-writing?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is markdown-mermaid-writing safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains markdown-mermaid-writing?

It is published by k-dense-ai in k-dense-ai/scientific-agent-skills. It has 2,107 recorded installs.

More from k-dense-ai/scientific-agent-skills

View all →

scientific-writing

k-dense-ai/scientific-agent-skills

Drafts, revises, and audits scientific manuscripts or reports with explicit evidence provenance, reporting-guideline coverage, authorship accountability, confidentiality controls, and local consistency checks. Use for manuscript sections, references, declarations, tables, figures, or submission preparation when scientific accuracy and traceability matter.

Education & Science2.4K installs

scientific-visualization

k-dense-ai/scientific-agent-skills

Creates and audits truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use it for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.

Education & Science2.4K installs

scientific-critical-thinking

k-dense-ai/scientific-agent-skills

Evaluates scientific claims and evidence quality. Applies to experimental design validity, biases and confounders, statistical interpretation, evidence grading frameworks (GRADE, Cochrane Risk of Bias), and teaching critical analysis. Supports evidence appraisal and identifying flaws; formal peer review writing belongs to peer-review.

Education & Science2.4K installs

literature-review

k-dense-ai/scientific-agent-skills

Conducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.

scientific-brainstorming

k-dense-ai/scientific-agent-skills

Facilitates evidence-aware scientific ideation with independent generation, structured discussion, explicit assumptions, transparent evaluation, adversarial review, and decision logs. Use for early-stage research brainstorming or prioritizing candidate directions; hand off empirical validation, study design, ethics or regulatory review, and clinical questions to appropriate experts or skills.

Education & Science2.3K installs

statistical-analysis

k-dense-ai/scientific-agent-skills

Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.

Testing & QA2.3K installs

Popular docs & writing skills

View category →

grill-with-docs

mattpocock/skills

A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

Docs & Writing1.2M installs

lark-markdown

open.feishu.cn

飞书 Markdown:查看、创建、上传、编辑和比较飞书中的原生 Markdown 文件。当用户要操作飞书 Markdown 文件,或比较其远端版本及本地草稿时使用。纯本地 Markdown 文件操作不触发本 skill。不负责将 Markdown 导入为飞书在线文档,也不负责文件搜索、权限、评论、移动、删除等云空间管理操作。

Docs & Writing778.7K installs

writing-beats

mattpocock/skills

Writing, exploit; assemble raw material into a journey of beats, grounding each term before a beat leans on it.

Docs & Writing490.7K installs

writing-shape

mattpocock/skills

Writing, exploit: shape raw material into an article, paragraph by paragraph.

Docs & Writing490.2K installs

writing-fragments

mattpocock/skills

Writing, explore: mine raw fragments, no structure yet.

Docs & Writing489.6K installs

writing-for-agents

mattpocock/skills

Writing documents for agents. Use when creating or editing skills, or modifying AGENTS.md or CLAUDE.md.

Docs & Writing479.3K installs