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Cto Advisor

skill-i-onlabs-claude-code-skills-cto-advisor · by I-Onlabs

Technical 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 use…

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Install

$ agentstack add skill-i-onlabs-claude-code-skills-cto-advisor

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

CTO Advisor

Strategic frameworks and tools for technology leadership, team scaling, and engineering excellence.

Keywords

CTO, chief technology officer, technical leadership, tech debt, technical debt, engineering team, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, ADR, architecture decision records, technology strategy, engineering leadership, engineering organization, team structure, hiring plan, technical strategy, vendor evaluation, technology selection

Quick Start

For Technical Debt Assessment

python scripts/tech_debt_analyzer.py

Analyzes system architecture and provides prioritized debt reduction plan.

For Team Scaling Planning

python scripts/team_scaling_calculator.py

Calculates optimal hiring plan and team structure for growth.

For Architecture Decisions

Review references/architecture_decision_records.md for ADR templates and examples.

For Technology Evaluation

Use framework in references/technology_evaluation_framework.md for vendor selection.

For Engineering Metrics

Implement KPIs from references/engineering_metrics.md for team performance tracking.

Core Responsibilities

1. Technology Strategy

Vision & Roadmap
  • Define 3-5 year technology vision
  • Create quarterly roadmaps
  • Align with business strategy
  • Communicate to stakeholders
Innovation Management
  • Allocate 20% time for innovation
  • Run hackathons quarterly
  • Evaluate emerging technologies
  • Build proof of concepts
Technical Debt Strategy
# Assess current debt
python scripts/tech_debt_analyzer.py

# Allocate capacity
- Critical debt: 40% capacity
- High debt: 25% capacity  
- Medium debt: 15% capacity
- Low debt: Ongoing maintenance

2. Team Leadership

Scaling Engineering
# Calculate scaling needs
python scripts/team_scaling_calculator.py

# Key ratios to maintain:
- Manager:Engineer = 1:8
- Senior:Mid:Junior = 3:4:2
- Product:Engineering = 1:10
- QA:Engineering = 1.5:10
Performance Management
  • Set clear OKRs quarterly
  • Conduct 1:1s weekly
  • Review performance quarterly
  • Provide growth opportunities
Culture Building
  • Define engineering values
  • Establish coding standards
  • Create learning programs
  • Foster collaboration

3. Architecture Governance

Decision Making

Use ADR template from references/architecture_decision_records.md:

  1. Document context and problem
  2. List all options considered
  3. Record decision and rationale
  4. Track consequences
Technology Standards
  • Language choices
  • Framework selection
  • Database standards
  • Security requirements
  • API design guidelines
System Design Review
  • Weekly architecture reviews
  • Design documentation standards
  • Prototype requirements
  • Performance criteria

4. Vendor Management

Evaluation Process

Follow framework in references/technology_evaluation_framework.md:

  1. Gather requirements (Week 1)
  2. Market research (Week 1-2)
  3. Deep evaluation (Week 2-4)
  4. Decision and documentation (Week 4)
Vendor Relationships
  • Quarterly business reviews
  • SLA monitoring
  • Cost optimization
  • Strategic partnerships

5. Engineering Excellence

Metrics Implementation

From references/engineering_metrics.md:

DORA Metrics (Deploy to production targets):

  • Deployment Frequency: >1/day
  • Lead Time: 80%
  • Code Review: 100%
  • Technical Debt: 99.9%
  • Deploy multiple times daily
  • Technical debt 8/10
  • Attrition 90%
  • Diversity improving

Business Impact

  • Features on-time >80%
  • Engineering enables revenue
  • Cost per transaction decreasing
  • Innovation driving growth

Red Flags to Watch

⚠️ Increasing technical debt ⚠️ Rising attrition rate ⚠️ Slowing velocity ⚠️ Growing incidents ⚠️ Team morale declining ⚠️ Budget overruns ⚠️ Vendor dependencies ⚠️ Security vulnerabilities

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.