CTO Advisor
Skill Verified ActiveTechnical leadership guidance for engineering teams, architecture decisions, and technology strategy. Includes tech debt analyzer, team scaling calculator, engineering metrics frameworks, technology evaluation tools, and ADR templates. Use when assessing technical debt, scaling engineering teams, evaluating technologies, making architecture decisions, establishing engineering metrics, or when user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
To empower engineering leaders with strategic frameworks and tools for making informed decisions about technology strategy, team growth, architecture, and technical debt.
Features
- Technical debt analysis and prioritization
- Team scaling calculation and hiring plans
- Architecture decision record templates and guidance
- Technology evaluation frameworks
- Engineering metrics and strategy guidance
Use Cases
- Assessing and planning technical debt reduction
- Calculating optimal team structure and hiring needs
- Making informed architecture decisions
- Evaluating and selecting new technologies
- Establishing engineering metrics and KPIs
Non-Goals
- Directly managing team tasks or code reviews
- Automating deployment or infrastructure changes
- Providing runtime monitoring or operational metrics
- Acting as a substitute for core engineering functions
Workflow
- Analyze current system state or team structure
- Generate scaling plan or technical debt assessment
- Review prioritized actions and recommendations
- Implement suggested changes and monitor outcomes
Practices
- Technical Strategy
- Team Leadership
- Architecture Governance
- Vendor Management
- Engineering Excellence
Prerequisites
- Python 3.7+ environment
- Basic understanding of engineering management concepts
Trust
- info:Issues AttentionThere are 17 open issues and 4 closed issues in the last 90 days, suggesting active development but also a backlog that could be addressed more promptly.
Code Execution
- info:ValidationThe Python scripts appear to handle dictionary inputs, but explicit schema validation libraries like Zod or Pydantic are not evident in the provided code snippets.
- info:Error HandlingThe Python scripts contain some basic error handling (e.g., division by zero checks), but comprehensive structured error reporting with retryable hints is not explicitly demonstrated.
Errors
- info:Actionable error messagesThe Python scripts include some basic error handling, but error messages are not consistently framed with remediation steps or doc links.
Execution
- info:Pinned dependenciesThe Python scripts are provided, but explicit dependency pinning and shebang/header declarations for interpreters and side effects are not clearly detailed.
Practical Utility
- info:Edge casesWhile the scripts handle some basic input scenarios, explicit documentation of failure modes, limitations, and recovery steps for edge cases is not extensively detailed.
Safety
- info:Halt on unexpected stateThe scripts include some basic checks, but explicit machine-readable preconditions and clear instructions to halt on unexpected pre-states are not fully documented.
Installation
npx skills add davila7/claude-code-templatesRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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