cto-advisor

Analyze engineering data to identify technical debt and team-scaling gaps.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/rickydwilson-dcs/claude-skills --skill cto-advisor-rickydwilson-dcs
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cto-advisor
Source: https://github.com/rickydwilson-dcs/claude-skills/tree/main/c-level-advisor/cto-advisor
Command: npx skills add https://github.com/rickydwilson-dcs/claude-skills --skill cto-advisor-rickydwilson-dcs

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

CTOs face immense pressure to manage technical debt, scale engineering teams, and define technology strategy. This Skill automates complex analyses and provides structured frameworks, freeing up time for strategic leadership and reducing the burden of manual planning.

Core Features & Use Cases

  • Technical Debt Analyzer: Quantify and prioritize technical debt across architecture, code, and infrastructure.
  • Team Scaling Calculator: Plan optimal hiring, team structure, and budget projections for engineering growth.
  • Use Case: When facing a critical system outage due to legacy architecture, use the tech_debt_analyzer.py to quickly assess the root causes and generate a prioritized remediation roadmap for executive review.

Quick Start

Use the cto-advisor skill to analyze the technical debt in 'system_data.json' and provide a prioritized reduction plan. Then, use it to calculate the optimal hiring plan for the engineering team described in 'team_data.json'.

Frequently Asked Questions about cto-advisor

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

FAQPage Schema
How do I quantify and prioritize technical debt across my engineering systems?

Technical debt quantification analyzes architecture, code, and infrastructure components to assign debt scores and prioritization. This Skill takes system JSON data and code metrics to identify the highest-impact areas for remediation, producing scored roadmaps for executive review and strategic planning.

What's the best way to plan engineering team scaling and hiring budgets?

Team scaling planning calculates optimal hiring levels, team structure, and budget projections based on engineering data. This Skill processes team metrics to generate structured hiring plans and growth forecasts aligned with technical roadmaps.

How do I use architecture decision records to guide technology strategy?

Architecture decision records (ADRs) document and track technology choices over time. This Skill ingests ADR records alongside system metrics to provide architecture guidance and evaluate technology decisions across projects, supporting informed strategy refinement.

Can I generate a prioritized remediation roadmap from legacy system data?

Yes. This Skill analyzes system JSON and code metrics to identify root causes of technical debt and output prioritized remediation roadmaps. Results include debt scores, governance artifacts, and structured recommendations for dashboard and report consumption.

What input formats and data do I need to assess technical debt?

Required inputs include system JSON describing architecture, code metrics quantifying complexity and dependencies, and ADR records documenting technology decisions. The Skill processes these structured inputs to produce debt scores, hiring plans, and prioritized action items.

Does this approach work for evaluating multiple projects and roadmaps simultaneously?

Yes. This Skill evaluates technology decisions and technical debt across projects and roadmaps, producing comparative governance artifacts. Multi-project analysis enables portfolio-level strategy and consistent debt reduction prioritization.