MCPInstall

cto-advisor

Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, or making architecture decisions.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/borghei/claude-skills --skill cto-advisor
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads cto-advisor automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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 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.

python scripts/tech_debt_analyzer.py --input system_config.json --json
python scripts/tech_debt_analyzer.py --input system_config.json
FlagTypeDescription
--inputoptionalPath to JSON file with system configuration (category indicators scored 0-100, team size, criticality, business context). Uses built-in example if omitted
--jsonoptionalOutput 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.

python scripts/team_scaling_calculator.py --input team_data.json --json
python scripts/team_scaling_calculator.py --input team_data.json
FlagTypeDescription
--inputoptionalPath to JSON file with current state (headcount, roles, velocity) and growth targets (target headcount, timeline). Uses built-in example if omitted
--jsonoptionalOutput in JSON format instead of human-readable text

Troubleshooting

ProblemLikely CauseResolution
Tech debt score increasing despite dedicated sprintsDebt reduction not keeping pace with new debt creationImplement debt prevention gates (code review, architecture review); track debt creation rate alongside reduction rate
DORA metrics improving but customer satisfaction decliningShipping faster but not shipping the right thingsAdd customer-impact metrics alongside DORA; review feature adoption rates; reconnect with product team on priorities
Team scaling plan keeps missing hiring targetsUnrealistic timeline, insufficient recruiting capacity, or poor employer brandAdjust timeline using 25% max quarterly growth rate; add recruiting resources (1 per 50 annual hires); invest in employer brand
Architecture decisions not documented or followedNo ADR process or ADRs created but not referencedImplement lightweight ADR template; make ADR review part of design review; link ADRs to relevant code
Engineering team morale declining during rapid growthCulture dilution, unclear expectations, or insufficient onboardingImplement structured onboarding; maintain 1:8 manager ratio; run quarterly team health surveys
Vendor lock-in creating strategic riskNo evaluation framework or over-reliance on single vendorRun 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

FAQ

What does the cto-advisor skill do?

Technical leadership guidance for engineering teams, architecture decisions, and technology strategy. Use when assessing technical debt, scaling engineering teams, evaluating technologies, or making architecture decisions.

How do I install cto-advisor?

Run npx skills add https://github.com/borghei/claude-skills --skill cto-advisor in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/cto-advisor/ (personal) or .claude/skills/cto-advisor/ (project).

Which AI agents can use cto-advisor?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is cto-advisor safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains cto-advisor?

It is published by borghei in borghei/claude-skills. It has 173 recorded installs.

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