cto-advisor

Analyze technical debt and calculate team scaling for engineering leadership.

Updated Mar 7, 2026

Search Tags:#architecture #tech debt #engineering metrics #team scaling #technical leadership #cto

Ready to run

npx skills add https://github.com/Geargrindadmin/gg-agentic-harness --skill cto-advisor-geargrindadmin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: cto-advisor
Source: https://github.com/Geargrindadmin/gg-agentic-harness/tree/main/.agent/skills/cto-advisor
Command: npx skills add https://github.com/Geargrindadmin/gg-agentic-harness --skill cto-advisor-geargrindadmin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scikit-learn, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides comprehensive guidance and tools for engineering leaders to address technical debt, scale teams effectively, make sound architecture decisions, and drive technology strategy.

Core Features & Use Cases

Technical Debt Analysis: Identifies and prioritizes technical debt with actionable insights.
Team Scaling Calculator: Helps plan optimal team structures and hiring.
Architecture Decision Records (ADR): Provides templates and guidance for documenting architectural choices.
Engineering Metrics Framework: Offers guidance on DORA metrics, productivity, and team health.
Use Case: A CTO needs to present a plan for reducing technical debt and scaling the engineering team to the board. This Skill can provide the analysis, metrics, and strategic frameworks needed for the presentation.

Quick Start

Run the tech debt analyzer script to assess the current state of your systems.

Frequently Asked Questions about cto-advisor

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

FAQPage Schema

How do I calculate optimal team scaling structures for an engineering organization?▼

Calculate optimal team scaling structures by inputting engineering data into the team scaling calculator, which outputs recommended hiring plans and team configurations to support organizational growth.

What is the best way to analyze and prioritize technical debt across my systems?▼

Analyze technical debt by running the tech debt analyzer script to identify systemic issues, prioritize them based on impact, and generate actionable insights for strategic remediation planning.

How do I implement engineering metrics frameworks for measuring team productivity?▼

Implement engineering metrics frameworks using the provided guidance on DORA metrics, productivity tracking, and team health indicators to quantify development performance.

Can I use architecture decision records to document technology evaluation choices?▼

Use architecture decision records to document technology evaluation choices through provided templates that capture architectural governance, context, and technical leadership decisions.

Do I need pandas and scikit-learn to run the technical debt analysis scripts?▼

You need pandas, numpy, and scikit-learn installed to run the technical debt analysis scripts, as these dependencies support the data processing and metric calculations.

When should I not use automated frameworks for architecture governance?▼

Avoid automated architecture governance frameworks when dealing with highly subjective architectural decisions requiring nuanced human judgment rather than template-driven technical leadership.