Markdown Mermaid Writing
Author research-grade markdown reports with embedded Mermaid flowcharts, checkpoints, and structured sections agents can reuse as a documentation standard.
Overview
Markdown Mermaid Writing is an agent skill most often used in Build (also Validate, Ship) that standardizes research-style markdown with embedded Mermaid diagrams and QC-gated workflow charts.
Install
npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill markdown-mermaid-writingWhat is this skill?
- Example CRISPR report shows Overview, workflow, and citation-friendly sections
- Mermaid flowcharts embed directly in markdown with accTitle and accDescr accessibility fields
- Five-stage experimental workflow template with explicit go/no-go QC decision nodes
- Demonstrates standardized headings and emoji section markers for scanability
- All diagrams specified as Mermaid-in-markdown source format per skill standards
- Example workflow: five-stage CRISPR pipeline with three explicit QC decision nodes
Adoption & trust: 613 installs on skills.sh; 27.6k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your agent writes long technical reports but diagrams are inconsistent, inaccessible, or not kept in markdown as the single source of truth.
Who is it for?
Indie builders and researchers who want agent-written lab notes, method docs, or analysis reports with inline Mermaid workflows.
Skip if: Pure slide decks, WYSIWYG-only doc tools, or UIs where Mermaid cannot render.
When should I use this skill?
You need agent-written technical or scientific markdown where diagrams must be Mermaid embedded in the same file as the prose.
What do I get? / Deliverables
Reports follow a documented markdown plus Mermaid pattern with titled flowcharts, stage gates, and sections ready for version control and publication.
- Structured markdown report
- Embedded Mermaid flowcharts with accTitle and accDescr
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Canonical shelf is Build docs because the skill defines how to write technical markdown artifacts agents produce during implementation and reporting. Docs subphase fits report structure, diagram syntax, and publication-ready prose rather than runtime code.
Where it fits
Document a bench protocol with QC gates before scaling the build.
Generate a CRISPR-style results memo with embedded stage flowchart.
Publish a release runbook whose deployment path is a single Mermaid flow in README.
How it compares
Use instead of unstructured markdown bullets when diagrams must stay editable text inside the same file as the narrative.
Common Questions / FAQ
Who is markdown-mermaid-writing for?
Solo builders and scientific or technical writers who want agents to emit consistent markdown reports with Mermaid diagrams.
When should I use markdown-mermaid-writing?
In Validate when documenting prototype methods; in Build when writing implementation or experiment docs; in Ship when packaging runbooks or release notes that need workflow diagrams.
Is markdown-mermaid-writing safe to install?
It is documentation guidance only; review the Security Audits panel on this page like any third-party skill before adding it to your agent bundle.
SKILL.md
READMESKILL.md - Markdown Mermaid Writing
# CRISPR-Based Gene Editing Efficiency Analysis _Example research report — demonstrates markdown-mermaid-writing skill standards. All diagrams use Mermaid embedded in markdown as the source format._ --- ## 📋 Overview This report analyzes the efficiency of CRISPR-Cas9 gene editing across three cell line models under variable guide RNA (gRNA) conditions. Editing efficiency was quantified by T7E1 assay and next-generation sequencing (NGS) of on-target loci[^1]. **Key findings:** - HEK293T cells show highest editing efficiency (mean 78%) across all gRNA designs - GC content between 40–65% correlates with editing efficiency (r = 0.82) - Off-target events occur at <0.1% frequency across all conditions tested --- ## 🔄 Experimental workflow CRISPR editing experiments followed a standardized five-stage protocol. Each stage has defined go/no-go criteria before proceeding. ```mermaid flowchart TD accTitle: CRISPR Editing Experimental Workflow accDescr: Five-stage experimental pipeline from gRNA design through data analysis, with quality checkpoints between each stage. design["🧬 Stage 1<br/>gRNA Design<br/>(CRISPRscan + Cas-OFFinder)"] synth["⚙️ Stage 2<br/>Oligo Synthesis<br/>& Annealing"] transfect["🔬 Stage 3<br/>Cell Transfection<br/>(Lipofectamine 3000)"] screen["🧪 Stage 4<br/>Primary Screen<br/>(T7E1 assay)"] ngs["📊 Stage 5<br/>NGS Validation<br/>(150 bp PE reads)"] qc1{GC 40-65%?} qc2{Yield ≥ 2 µg?} qc3{Viability ≥ 85%?} qc4{Band visible?} design --> qc1 qc1 -->|"✅ Pass"| synth qc1 -->|"❌ Redesign"| design synth --> qc2 qc2 -->|"✅ Pass"| transfect qc2 -->|"❌ Re-synthesize"| synth transfect --> qc3 qc3 -->|"✅ Pass"| screen qc3 -->|"❌ Optimize"| transfect screen --> qc4 qc4 -->|"✅ Pass"| ngs qc4 -->|"❌ Repeat"| screen classDef stage fill:#dbeafe,stroke:#2563eb,stroke-width:2px,color:#1e3a5f classDef gate fill:#fef9c3,stroke:#ca8a04,stroke-width:2px,color:#713f12 classDef fail fill:#fee2e2,stroke:#dc2626,stroke-width:2px,color:#7f1d1d class design,synth,transfect,screen,ngs stage class qc1,qc2,qc3,qc4 gate ``` --- ## 🔬 Methods ### Cell lines and culture Three cell lines were used: HEK293T (human embryonic kidney), K562 (chronic myelogenous leukemia), and Jurkat (T-lymphocyte). All lines were maintained in RPMI-1640 with 10% FBS at 37°C / 5% CO₂[^2]. ### gRNA design and efficiency prediction gRNAs targeting the _EMX1_ locus were designed using CRISPRscan[^3] with the following criteria: | Criterion | Threshold | Rationale | | -------------------- | --------- | ------------------------------------- | | GC content | 40–65% | Optimal Tm and Cas9 binding | | CRISPRscan score | ≥ 0.6 | Predicted on-target activity | | Off-target sites | ≤ 5 (≤3 mismatches) | Reduce off-target editing risk | | Homopolymer runs | None (>4 nt) | Prevents premature transcription stop | ### Transfection protocol RNP complexes were assembled at 1:1.2 molar ratio (Cas9:gRNA) and delivered by lipofection. Cells were harvested 72 hours post-transfection for genomic DNA extraction. ### Analysis pipeline ```mermaid sequenceDiagram accTitle: NGS Data Analysis Pipeline accDescr: Sequence of computational steps from raw FASTQ files through variant calling to final efficiency report. participant raw as 📥 Raw FASTQ participant qc as 🔍 FastQC participant trim as ✂️ Trimmomatic participant align as 🗺️ BWA-MEM2 participant call as ⚙️ CRISPResso2 participant report as 📊 Report raw->>qc: Per-base quality scores qc-->>trim: Flag low-Q reads (Q<20) trim->>align: Cleaned reads align->>align: Index reference genome (hg38) align->>call: BAM + target region BED call->>call: Quantify indel frequency call-->>report: Editing efficiency (%) call-->>report: Off-target events report-->>report: Statistical summary ``` --- ## 📊 Results ### Editing efficiency by cell line |