pipeline-graph-builder

Construct business-level DAGs from code analysis results using Python and NetworkX.

Updated Jun 2, 2026
One-click install
npx skills add https://github.com/bettercallfan/deerflow --skill pipeline-graph-builder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pipeline-graph-builder
Source: https://github.com/bettercallfan/deerflow/tree/main/skills/custom/program_snippet/pipeline-graph-builder
Command: npx skills add https://github.com/bettercallfan/deerflow --skill pipeline-graph-builder

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, networkx, and includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of manually constructing and maintaining complex business-level Directed Acyclic Graphs (DAGs) from code analysis results.

Core Features & Use Cases

  • Automated DAG Construction: Automatically generates a business-level DAG from code analysis results such as calls, dataflow, and labeled nodes.
  • Integration with DeerFlow: Seamlessly integrates with the DeerFlow platform for a comprehensive code analysis and orchestration experience.
  • Use Case: Ideal for developers and system architects who need to visualize and manage the dependencies and data flows within their codebase.

Quick Start

Build a business-level DAG from the given calls, dataflow, and labeled nodes using the pipeline-graph-builder skill.

Frequently Asked Questions about pipeline-graph-builder

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a business-level DAG from code analysis results?▼

To build a business-level DAG from code analysis results, you can use a pipeline-graph-builder to automatically construct the graph from your calls, dataflow, and labeled nodes. It automates visualizing and managing code dependencies.

What is a business-level Directed Acyclic Graph used for in code analysis?▼

A business-level Directed Acyclic Graph in code analysis is used to visualize and manage dependencies and data flows within a codebase. It represents complex structural relationships extracted from calls and dataflow.

Do I need Python and NetworkX to construct a DAG from dataflow and calls?▼

Yes, you need Python and NetworkX to construct a DAG from dataflow and calls using this skill. NetworkX provides the necessary graph construction and orchestration capabilities required to generate the business-level dependencies.

Can I use this pipeline graph builder within the DeerFlow platform?▼

Yes, this pipeline graph builder is designed for seamless integration within the DeerFlow platform. It provides a comprehensive code analysis and orchestration experience by automating dependency and data flow visualization.

What's the best way to automate code dependency visualization for system architects?▼

The best way to automate code dependency visualization for system architects is to automatically generate a business-level DAG from code analysis. This approach transforms raw calls and dataflow into a managed, visual representation of codebase structure.