Best use case
bmorphism-diagrams is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
bmorphism Diagrams
Teams using bmorphism-diagrams should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/bmorphism-diagrams/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How bmorphism-diagrams Compares
| Feature / Agent | bmorphism-diagrams | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
bmorphism Diagrams
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# bmorphism Diagrams
Interleave bmorphism's mermaid diagrams into interactions using GF(3) triadic selection.
## Data Source
```
~/mermaid_diagrams.duckdb
├── diagrams (251 rows)
│ ├── id: UUID
│ ├── content: VARCHAR (mermaid code)
│ ├── diagram_type: VARCHAR (graph|flowchart|stateDiagram|...)
│ ├── trit: INTEGER (-1, 0, +1)
│ └── content_hash: VARCHAR
```
## Diagram Types
| Type | Count | Use Case |
|------|-------|----------|
| graph | 126 | Dependency/skill relationships |
| flowchart | 47 | Process flows, architectures |
| stateDiagram | 8 | State machines, protocols |
| sequenceDiagram | 6 | Message passing, APIs |
| classDiagram | 6 | Type hierarchies |
| pie | 2 | Distribution stats |
| erDiagram | 1 | Data models |
## Interleaving Protocol
### 1. Random Selection (Entropy-Seeded)
```bash
# Get random diagram by trit
duckdb ~/mermaid_diagrams.duckdb "
SELECT content FROM diagrams
WHERE trit = (SELECT (random() * 3 - 1)::int % 3)
ORDER BY random() LIMIT 1
"
```
### 2. Type-Matched Selection
```bash
# Match diagram type to context
duckdb ~/mermaid_diagrams.duckdb "
SELECT content FROM diagrams
WHERE diagram_type = 'flowchart'
ORDER BY random() LIMIT 1
"
```
### 3. GF(3) Balanced Triad
```bash
# Get one diagram per trit for balanced presentation
duckdb ~/mermaid_diagrams.duckdb "
(SELECT content, trit FROM diagrams WHERE trit = -1 ORDER BY random() LIMIT 1)
UNION ALL
(SELECT content, trit FROM diagrams WHERE trit = 0 ORDER BY random() LIMIT 1)
UNION ALL
(SELECT content, trit FROM diagrams WHERE trit = 1 ORDER BY random() LIMIT 1)
"
```
## Usage Triggers
Interleave a bmorphism diagram when:
1. **Architecture discussions** → flowchart/graph
2. **Protocol design** → sequenceDiagram/stateDiagram
3. **Data modeling** → erDiagram/classDiagram
4. **Skill loading** → graph (skill dependencies)
5. **Random inspiration** → any type, entropy-seeded
## Rendering
Use the `mermaid` tool to render selected diagrams:
```
mermaid(code=DIAGRAM_CONTENT, citations={})
```
## Example Workflow
```bash
# 1. Query a contextual diagram
DIAGRAM=$(duckdb ~/mermaid_diagrams.duckdb -noheader -list "
SELECT content FROM diagrams
WHERE diagram_type = 'flowchart'
AND content LIKE '%GF(3)%'
ORDER BY random() LIMIT 1
")
# 2. Render via mermaid tool
# mermaid(code=$DIAGRAM, citations={})
```
## Trit Assignment
Diagrams inherit trits from content analysis:
- **MINUS (-1)**: Validation, constraints, error states
- **ERGODIC (0)**: Neutral flows, queries, observations
- **PLUS (+1)**: Generation, creation, composition
## Stats Query
```bash
duckdb ~/mermaid_diagrams.duckdb "
SELECT
diagram_type,
COUNT(*) as count,
SUM(CASE WHEN trit = -1 THEN 1 ELSE 0 END) as minus,
SUM(CASE WHEN trit = 0 THEN 1 ELSE 0 END) as ergodic,
SUM(CASE WHEN trit = 1 THEN 1 ELSE 0 END) as plus
FROM diagrams
GROUP BY diagram_type
ORDER BY count DESC
"
```
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Graph Theory
- **networkx** [○] via bicomodule
- Hub for all graph/network skills
### Visualization
- **matplotlib** [○] via bicomodule
- Scientific visualization
### Bibliography References
- `general`: 734 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
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