pm-graph

Parse wiki-links and compute connectivity metrics for PM decision graphs.

Updated Feb 3, 2026
One-click install
npx skills add https://github.com/LopeWale/amplLABS --skill pm-graph
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pm-graph
Source: https://github.com/LopeWale/amplLABS/tree/main/.claude/skills/pm-graph
Command: npx skills add https://github.com/LopeWale/amplLABS --skill pm-graph

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Visualize and analyze decision graphs to reveal connections, identify clusters, trace lineage, and surface central nodes in a PM knowledge base.

Core Features & Use Cases

  • Overview: Generate a graph overview showing all decisions and their connections.
  • Lineage Trace: Trace the full lineage for a specific decision.
  • Cluster & Centrality: Identify topic clusters and highly connected decisions to reveal architectural hubs.
  • Use Case: In a PM system with 50 decisions and 200 links, quickly map dependencies and identify bottlenecks.

Quick Start

Ask pm-graph to generate an overview of all decisions or a lineage trace for a specific decision.

Frequently Asked Questions about pm-graph

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

FAQPage Schema
How do I trace the lineage of a specific decision in a knowledge base?

To trace decision lineage, the Skill computes connectivity metrics and outputs a text-based representation of all linked nodes for that specific decision. It parses wiki-links to map dependencies without needing a visual tool.

What is the best way to visualize decision graphs and identify topic clusters?

Visualizing decision graphs is achieved by applying graph analysis to compute connectivity and output text-based representations. This process identifies topic clusters and surfaces central architectural hubs within the knowledge base.

Can I analyze PM decision graphs without a dedicated visual tool?

Yes, you can analyze PM decision graphs without a visual tool by generating text-based representations. The Skill parses wiki-links and computes connectivity metrics to reveal connections, clusters, and lineage directly.

How do I find highly connected decisions and bottlenecks in a PM system?

Finding highly connected decisions relies on computing centrality and connectivity metrics across the graph. This surfaces central nodes and architectural hubs, allowing you to quickly map dependencies and identify bottlenecks.

Does pm-graph work with large knowledge bases containing hundreds of wiki-links?

Yes, pm-graph scales to handle large PM systems, such as a knowledge base with 50 decisions and 200 wiki-links. It parses these links to generate an overview of all decisions and trace specific lineage connections.