library/specializations/software-architecture/skills/dependency-graph-generator/SKILL.md
Generate module dependency graphs with circular dependency detection and coupling metrics
npx skillsauth add a5c-ai/babysitter dependency-graph-generatorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Generates module dependency graphs with circular dependency identification, coupling metrics calculation, and visualization output in Graphviz or D3 formats.
{
"type": "object",
"required": ["entryPoints"],
"properties": {
"entryPoints": {
"type": "array",
"items": { "type": "string" },
"description": "Entry point files or directories"
},
"outputFormat": {
"type": "string",
"enum": ["dot", "json", "d3", "mermaid"],
"default": "dot"
},
"outputPath": {
"type": "string",
"description": "Output file path"
},
"options": {
"type": "object",
"properties": {
"depth": {
"type": "number",
"default": -1,
"description": "Maximum depth (-1 for unlimited)"
},
"includeExternal": {
"type": "boolean",
"default": false
},
"groupByPackage": {
"type": "boolean",
"default": true
},
"detectCircular": {
"type": "boolean",
"default": true
}
}
}
}
}
{
"type": "object",
"properties": {
"graph": {
"type": "object",
"properties": {
"nodes": { "type": "array" },
"edges": { "type": "array" }
}
},
"circularDependencies": {
"type": "array",
"items": {
"type": "array",
"items": { "type": "string" }
}
},
"metrics": {
"type": "object",
"properties": {
"totalModules": { "type": "number" },
"totalDependencies": { "type": "number" },
"averageCoupling": { "type": "number" }
}
},
"outputPath": {
"type": "string"
}
}
}
{
kind: 'skill',
skill: {
name: 'dependency-graph-generator',
context: {
entryPoints: ['src/index.ts'],
outputFormat: 'dot',
outputPath: 'docs/dependencies.dot',
options: {
groupByPackage: true,
detectCircular: true
}
}
}
}
development
Model documentation skill for generating model cards following Google's model card framework.
development
MLflow integration skill for experiment tracking, model registry, and artifact management. Enables LLMs to log experiments, compare runs, manage model lifecycle, and retrieve artifacts through the MLflow API.
data-ai
LIME-based local explanation skill for individual predictions across tabular, text, and image data.
devops
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.