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 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.

33 stars

Best use case

cto-advisor is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using cto-advisor should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/cto-advisor/SKILL.md --create-dirs "https://raw.githubusercontent.com/aAAaqwq/AGI-Super-Team/main/skills/cto-advisor/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cto-advisor/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How cto-advisor Compares

Feature / Agentcto-advisorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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
```bash
python scripts/tech_debt_analyzer.py
```
Analyzes system architecture and provides prioritized debt reduction plan.

### For Team Scaling Planning
```bash
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
```bash
# 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
```bash
# 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 security team
- Legal/compliance notification
- Customer communication plan

#### Major Outage
- All-hands response
- Status page updates
- Executive briefings
- Customer outreach

#### Data Loss
- Stop writes immediately
- Assess recovery options
- Begin restoration
- Impact analysis

## Stakeholder Management

### Board/Executive Reporting
**Monthly**:
- KPI dashboard
- Risk register
- Major initiatives status

**Quarterly**:
- Technology strategy update
- Team growth and health
- Innovation highlights
- Budget review

### Cross-functional Partners

#### Product Team
- Weekly roadmap sync
- Sprint planning participation
- Technical feasibility reviews
- Feature estimation

#### Sales/Marketing
- Technical sales support
- Product capability briefings
- Customer reference calls
- Competitive analysis

#### Finance
- Budget management
- Cost optimization
- Vendor negotiations
- Capex planning

## Strategic Initiatives

### Digital Transformation
1. Assess current state
2. Define target architecture
3. Create migration plan
4. Execute in phases
5. Measure and adjust

### Cloud Migration
1. Application assessment
2. Migration strategy (7Rs)
3. Pilot applications
4. Full migration
5. Optimization

### Platform Engineering
1. Define platform vision
2. Build core services
3. Create self-service tools
4. Enable team adoption
5. Measure efficiency

### AI/ML Integration
1. Identify use cases
2. Build data infrastructure
3. Develop models
4. Deploy and monitor
5. Scale adoption

## Communication Templates

### Technology Strategy Presentation
```
1. Executive Summary (1 slide)
2. Current State Assessment (2 slides)
3. Vision & Strategy (2 slides)
4. Roadmap & Milestones (3 slides)
5. Investment Required (1 slide)
6. Risks & Mitigation (1 slide)
7. Success Metrics (1 slide)
```

### Team All-hands
```
1. Wins & Recognition (5 min)
2. Metrics Review (5 min)
3. Strategic Updates (10 min)
4. Demo/Deep Dive (15 min)
5. Q&A (10 min)
```

### Board Update Email
```
Subject: Engineering Update - [Month]

Highlights:
• [Major achievement]
• [Key metric improvement]
• [Strategic progress]

Challenges:
• [Issue and mitigation]

Next Month:
• [Priority 1]
• [Priority 2]

Detailed metrics attached.
```

## Tools & Resources

### Essential Tools
- **Architecture**: Draw.io, Lucidchart, C4 Model
- **Metrics**: DataDog, Grafana, LinearB
- **Planning**: Jira, Confluence, Notion
- **Communication**: Slack, Zoom, Loom
- **Development**: GitHub, GitLab, Bitbucket

### Key Resources
- **Books**: 
  - "The Manager's Path" - Camille Fournier
  - "Accelerate" - Nicole Forsgren
  - "Team Topologies" - Skelton & Pais
  
- **Frameworks**:
  - DORA metrics
  - SPACE framework
  - Team Topologies
  
- **Communities**:
  - CTO Craft
  - Engineering Leadership Slack
  - LeadDev community

## Success Indicators

✅ **Technical Excellence**
- System uptime >99.9%
- Deploy multiple times daily
- Technical debt <10% capacity
- Security incidents = 0

✅ **Team Success**
- Team satisfaction >8/10
- Attrition <10%
- Filled positions >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

---

## Tool Reference

### 1. tech_debt_analyzer.py

Analyzes system architecture for technical debt across 5 categories (architecture, code quality, infrastructure, security, performance). Calculates weighted debt scores, prioritizes reduction actions, estimates effort, and assesses risk levels.

```bash
python scripts/tech_debt_analyzer.py --input system_config.json --json
python scripts/tech_debt_analyzer.py --input system_config.json
```

| Flag | Type | Description |
|------|------|-------------|
| `--input` | optional | Path to JSON file with system configuration (category indicators scored 0-100, team size, criticality, business context). Uses built-in example if omitted |
| `--json` | optional | Output in JSON format instead of human-readable text |

### 2. team_scaling_calculator.py

Calculates optimal engineering team scaling plans including hiring timeline, role distribution, team structure design, budget projections, and risk assessment. Applies Brooks' Law and Conway's Law factors.

```bash
python scripts/team_scaling_calculator.py --input team_data.json --json
python scripts/team_scaling_calculator.py --input team_data.json
```

| Flag | Type | Description |
|------|------|-------------|
| `--input` | optional | Path to JSON file with current state (headcount, roles, velocity) and growth targets (target headcount, timeline). Uses built-in example if omitted |
| `--json` | optional | Output in JSON format instead of human-readable text |

---

## Troubleshooting

| Problem | Likely Cause | Resolution |
|---------|-------------|------------|
| Tech debt score increasing despite dedicated sprints | Debt reduction not keeping pace with new debt creation | Implement debt prevention gates (code review, architecture review); track debt creation rate alongside reduction rate |
| DORA metrics improving but customer satisfaction declining | Shipping faster but not shipping the right things | Add customer-impact metrics alongside DORA; review feature adoption rates; reconnect with product team on priorities |
| Team scaling plan keeps missing hiring targets | Unrealistic timeline, insufficient recruiting capacity, or poor employer brand | Adjust timeline using 25% max quarterly growth rate; add recruiting resources (1 per 50 annual hires); invest in employer brand |
| Architecture decisions not documented or followed | No ADR process or ADRs created but not referenced | Implement lightweight ADR template; make ADR review part of design review; link ADRs to relevant code |
| Engineering team morale declining during rapid growth | Culture dilution, unclear expectations, or insufficient onboarding | Implement structured onboarding; maintain 1:8 manager ratio; run quarterly team health surveys |
| Vendor lock-in creating strategic risk | No evaluation framework or over-reliance on single vendor | Run technology evaluation for critical vendors; implement abstraction layers; maintain exit strategies |

---

## Success Criteria

- Tech debt score below 40 (Medium-Low) across all categories
- DORA metrics at "High" or "Elite" performance tier (deployment frequency > weekly, lead time < 1 week, MTTR < 1 day, change failure rate < 15%)
- Team balance score above 70/100 with appropriate role ratios maintained
- Architecture decisions documented via ADRs for all significant technical choices
- System uptime exceeds 99.9% for production systems
- Engineering team satisfaction above 8/10 with attrition below 10%
- Innovation time (hackathons, exploration) maintained at 15-20% of engineering capacity

---

## Scope & Limitations

**In scope:** Technology strategy and vision, technical debt assessment and reduction planning, engineering team scaling and structure design, architecture governance (ADRs, design reviews), vendor management and evaluation, engineering metrics (DORA, quality, team health), crisis management (incident response, security breach, data loss), stakeholder management and board reporting, and strategic initiatives (cloud migration, platform engineering, AI/ML integration).

**Out of scope:** Hands-on coding or code review (use engineering/ skills), product feature prioritization (use cpo-advisor), security architecture and compliance (use ciso-advisor or ra-qm-team/), HR policy and compensation design (use chro-advisor or hr-operations/), and financial planning for engineering budget (use cfo-advisor). Tools analyze engineering data snapshots; continuous metrics tracking requires integration with DevOps platforms.

**Limitations:** Tech debt scoring depends on self-reported indicator data; automated code analysis tools provide more objective measures. Team scaling budget projections use average salary bands that vary significantly by location, seniority mix, and market conditions. DORA benchmarks assume standard software delivery practices; hardware or embedded systems teams may need different targets.

---

## Integration Points

- **ceo-advisor** -- Technology strategy aligns with business direction; engineering capacity enables or constrains strategic bets
- **cpo-advisor** -- Technical feasibility co-owned with CPO; features vs platform trade-offs require joint decision-making
- **cfo-advisor** -- Engineering budget, headcount costs, and vendor spend feed financial planning
- **coo-advisor** -- System reliability and incident response intersect with operational excellence
- **ciso-advisor** -- Security architecture, vulnerability management, and compliance require CISO partnership
- **engineering/** -- CTO strategy cascades to engineering team execution; architecture decisions guide implementation

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