LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Comprehensive markdown and Mermaid diagram writing skill that establishes text-based diagrams as the DEFAULT documentation standard. Use this skill when creating ANY scientific document, report, analysis, or visualization — it ensures all outputs are in version-controlled,
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill markdown-mermaid-writing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/markdown-mermaid-writingContext preview
The summary Claude sees to decide when to auto-load this skill.
Comprehensive markdown and Mermaid diagram writing skill that establishes text-based diagrams as the DEFAULT documentation standard. Use this skill when creating ANY scientific document, report, analysis, or visualization — it ensures all outputs are in version-controlled,
name: markdown-mermaid-writing
description: >
Comprehensive markdown and Mermaid diagram writing skill that establishes text-based
diagrams as the DEFAULT documentation standard. Use this skill when creating ANY
scientific document, report, analysis, or visualization — it ensures all outputs are
in version-controlled, token-efficient markdown with embedded Mermaid diagrams as the
source of truth, with clear pathways to downstream Python or AI-generated images.
Includes full style guides (markdown + mermaid), 24 diagram type references, and
9 document templates ready to use.
allowed-tools: Read Write Edit Bash
license: Apache-2.0
metadata:
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:
- name: Clayton Young
org: Superior Byte Works, LLC / @borealBytes
role: Author and originator
- name: K-Dense Team
org: K-Dense Inc.
role: Integration target and community feedbackThis 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
Use this skill when:
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).
| 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 |
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.
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` | | Requi
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Repo: foryourhealth111-pixel/Vibe-Skills
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
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