/pave-catalog

PavePlatform Engineering

Builds a service catalog: inventories all services with their owners, descriptions, tech stacks, upstream and downstream dependencies, health status endpoints, and documentation links. Can be implemented in Backstage, a static site, or a structured document depending on team size and tooling.

Install

This skill

Install Pave Catalog

1. Add to marketplace

$ claude plugin marketplace add tonone-ai/tonone

2. Install this skill

$ claude plugin install pave-catalog@tonone-ai

The agent

Install Pave

1. Add to marketplace

$ claude plugin marketplace add tonone-ai/tonone

2. Install Pave

$ claude plugin install pave@tonone-ai

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Full installation guide

Invoke this skill

Command|$ /pave-catalog

When to use

When the team does not have a clear picture of what services exist and who is responsible for each one. When making changes to a service and need to know what depends on it before proceeding. When onboarding engineers need a map of the system before they can contribute confidently.

Deep dive

AI Service Catalog Design

Teams cannot operate what they cannot inventory. /pave-catalog builds a service catalog with owners, dependencies, health endpoints, and docs links.

Read the article

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Builds a golden path template for a specific service type: includes project scaffolding, local dev setup with one-command startup, CI pipeline, deployment configuration, and monitoring instrumentation baked in from the start. New services created from it start correctly and consistently.

When the team creates new services frequently and …

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/pave-env

Sets up local development environments with devcontainer configuration, Docker Compose service definitions that match production, and one-command startup so every developer has a consistent environment from day one. Addresses the 'works on my machine' problem systematically rather than with workarounds.

When local setup is undocumented, takes hours, or …

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/pave-audit

Audits developer experience by measuring the things that slow developers down: time to first working local environment, build times at different cache states, deployment friction from commit to production, test execution speed, and time to first production deploy for a new feature. Uses DORA metrics as a framework.

When developers are slowed down by tooling but it …

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