/cto-advisor
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
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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
SKILL.md
cto-advisor.SKILL.mdname: cto-advisor
description: 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 user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy.
license: MIT
metadata:
version: 1.0.0
author: Alireza Rezvani
category: c-level
domain: cto-leadership
updated: 2025-10-20
python-tools: tech_debt_analyzer.py, team_scaling_calculator.py
frameworks: DORA-metrics, architecture-decision-records, engineering-metrics
tech-stack: engineering-management, team-organization
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: <1 day
- MTTR: <1 hour
- Change Failure Rate: <15%
**Quality Metrics**:
- Test Coverage: >80%
- Code Review: 100%
- Technical Debt: <10%
**Team Health**:
- Sprint Velocity: ±10% variance
- Unplanned Work: <20%
- On-call Incidents: <5/week
Weekly Cadence
Monday
- Leadership team sync
- Review metrics dashboard
- Address escalations
Tuesday
- Architecture review
- Technical interviews
- 1:1s with directs
Wednesday
- Cross-functional meetings
- Vendor meetings
- Strategy work
Thursday
- Team all-hands (monthly)
- Sprint reviews (bi-weekly)
- Technical deep dives
Friday
- Strategic planning
- Innovation time
- Week recap and planning
Quarterly Planning
Q1 Focus: Foundation
- Annual planning
- Budget allocation
- Team goal setting
- Technology assessment
Q2 Focus: Execution
- Major initiatives launch
- Mid-year hiring push
- Performance reviews
- Architecture evolution
Q3 Focus: Innovation
- Hackathon
- Technology exploration
- Team development
- Process optimization
Q4 Focus: Planning
- Next year strategy
- Budget planning
- Promotion cycles
- Debt reduction sprint
Crisis Management
Incident Response
1. **Immediate** (0-15 min):
- Assess severity
- Activate incident team
- Begin communication
2. **Short-term** (15-60 min):
- Implement fixes
- Update stakeholders
- Monitor systems
3. **Resolution** (1-24 hours):
- Verify fix
- Document timeline
- Customer communication
4. **Post-mortem** (48-72 hours):
- Root cause analysis
- Action items
- Process improvements
Types of Crises
Security Breach
- Isolate affected systems
- Engage secur
Read more
name: cto-advisor description: 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 user mentions CTO, tech debt, technical debt, team scaling, architecture decisions, technology evaluation, engineering metrics, DORA metrics, or technology strategy. license: MIT metadata: version: 1.0.0 author: Alireza Rezvani category: c-level domain: cto-leadership updated: 2025-10-20 python-tools: tech_debt_analyzer.py, team_scaling_calculator.py frameworks: DORA-metrics, architecture-decision-records, engineering-metrics tech-stack: engineering-management, team-organization
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: <1 day
- MTTR: <1 hour
- Change Failure Rate: <15%
**Quality Metrics**:
- Test Coverage: >80%
- Code Review: 100%
- Technical Debt: <10%
**Team Health**:
- Sprint Velocity: ±10% variance
- Unplanned Work: <20%
- On-call Incidents: <5/week
Weekly Cadence
Monday
- Leadership team sync
- Review metrics dashboard
- Address escalations
Tuesday
- Architecture review
- Technical interviews
- 1:1s with directs
Wednesday
- Cross-functional meetings
- Vendor meetings
- Strategy work
Thursday
- Team all-hands (monthly)
- Sprint reviews (bi-weekly)
- Technical deep dives
Friday
- Strategic planning
- Innovation time
- Week recap and planning
Quarterly Planning
Q1 Focus: Foundation
- Annual planning
- Budget allocation
- Team goal setting
- Technology assessment
Q2 Focus: Execution
- Major initiatives launch
- Mid-year hiring push
- Performance reviews
- Architecture evolution
Q3 Focus: Innovation
- Hackathon
- Technology exploration
- Team development
- Process optimization
Q4 Focus: Planning
- Next year strategy
- Budget planning
- Promotion cycles
- Debt reduction sprint
Crisis Management
Incident Response
1. **Immediate** (0-15 min):
- Assess severity
- Activate incident team
- Begin communication
2. **Short-term** (15-60 min):
- Implement fixes
- Update stakeholders
- Monitor systems
3. **Resolution** (1-24 hours):
- Verify fix
- Document timeline
- Customer communication
4. **Post-mortem** (48-72 hours):
- Root cause analysis
- Action items
- Process improvements
Types of Crises
Security Breach
- Isolate affected systems
- Engage secur
Multi-agent orchestration system for Claude Code with parallel execution, automated quality gates, Board of Directors, and bundled Superpowers skills
Repo: Ibrahim-3d/orchestrator-supaconductor
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You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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