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Cto Advisor

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Ibrahim-3d
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.

Overview

PublisherIbrahim-3d
Repositoryorchestrator-supaconductor
Skill namecto-advisor
Stars
378
Forks
38
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Ibrahim-3d on GitHub. Read the source before you install it.

Installation

Install the Cto Advisor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Ibrahim-3d/orchestrator-supaconductor.git /tmp/orchestrator-supaconductor
mkdir -p .claude/skills
cp -r /tmp/orchestrator-supaconductor/skills/cto-advisor .claude/skills/cto-advisor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cto Advisor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cto Advisor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cto Advisor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cto Advisor AI 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.

Why use Cto Advisor on TypingMind?

Because you install it once and use it with any model. Cto Advisor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cto Advisor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Ibrahim-3d/orchestrator-supaconductor/tree/master/skills/cto-advisor. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cto Advisor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cto Advisor?

As many as you like. As long as a model supports skills, you can use Cto Advisor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cto Advisor AI skill free?

Yes. It is published on GitHub by Ibrahim-3d under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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