artifacts/bundle/skills/c-level-advisor/cto-advisor/SKILL.md
> **Note:** Bundled scripts ship as Markdown reference (`.md`) — copy the code out of the `.md` file to run it. # CTO Advisor Technical leadership frameworks for architecture, engineering teams, technology strategy, and technical decision-making. ## Keywords CTO, chief technology officer, tech debt, technical debt, architecture, engineering metrics, DORA, team scaling, technology evaluation, build vs buy, cloud migration, platform engineering, AI/ML strategy, system design, incident response
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Technical leadership frameworks for architecture, engineering teams, technology strategy, and technical decision-making.
CTO, chief technology officer, tech debt, technical debt, architecture, engineering metrics, DORA, team scaling, technology evaluation, build vs buy, cloud migration, platform engineering, AI/ML strategy, system design, incident response, engineering culture
python scripts/tech_debt_analyzer.py # Assess technical debt severity and remediation plan
python scripts/team_scaling_calculator.py # Model engineering team growth and cost
Align technology investments with business priorities.
Strategy components:
See references/technology_evaluation_framework.md for the full evaluation framework.
Scale the engineering org's productivity — not individual output.
Scaling engineering:
Culture:
See references/engineering_metrics.md for DORA metrics and the engineering health dashboard.
Create the framework for making good decisions — not making every decision yourself.
Architecture Decision Records (ADRs):
See references/architecture_decision_records.md for ADR templates and the decision review process.
Every vendor is a dependency. Every dependency is a risk.
Evaluation criteria: Does it solve a real problem? Can we migrate away? Is the vendor stable? What's the total cost (license + integration + maintenance)?
Incident response, security breaches, major outages, data loss.
Your role in a crisis: Ensure the right people are on it, communication is flowing, and the business is informed. Post-crisis: blameless retrospective within 48 hours.
Step 1 — Run the analyzer
python scripts/tech_debt_analyzer.py --output report.json
Step 2 — Interpret results The analyzer produces a severity-scored inventory. Review each item against:
Step 3 — Build a prioritized remediation plan
Sort by: (Severity × Blast Radius) / Cost-to-fix — highest score = fix first.
Group items into: (a) immediate sprint, (b) next quarter, (c) tracked backlog.
Step 4 — Validate before presenting to stakeholders
Example output — Tech Debt Inventory:
Item | Severity | Cost-to-Fix | Blast Radius | Priority Score
----------------------|----------|-------------|--------------|---------------
Auth service (v1 API) | P1 | 8 days | 6 services | HIGH
Unindexed DB queries | P2 | 3 days | 2 services | MEDIUM
Legacy deploy scripts | P3 | 5 days | 1 service | LOW
Step 1 — Identify the decision Trigger an ADR when: the decision affects more than one team, is hard to reverse, or has cost/risk implications > 1 sprint of effort.
Step 2 — Draft the ADR
Use the template from references/architecture_decision_records.md:
Title: [Short noun phrase]
Status: Proposed | Accepted | Superseded
Context: What is the problem? What constraints exist?
Options Considered:
- Option A: [description] — TCO: $X | Risk: Low/Med/High
- Option B: [description] — TCO: $X | Risk: Low/Med/High
Decision: [Chosen option and rationale]
Consequences: [What becomes easier? What becomes harder?]
Step 3 — Validation checkpoint (before finalizing)
Step 4 — Communicate and close Share the accepted ADR in the engineering all-hands or architecture sync. Link it from the relevant service's README.
Step 1 — Define requirements (functional + non-functional) Step 2 — Identify candidate vendors or internal build scope Step 3 — Score each option:
Criterion | Weight | Build Score | Vendor A Score | Vendor B Score
-----------------------|--------|-------------|----------------|---------------
Solves core problem | 30% | 9 | 8 | 7
Migration risk | 20% | 2 (low risk)| 7 | 6
3-year TCO | 25% | $X | $Y | $Z
Vendor stability | 15% | N/A | 8 | 5
Integration effort | 10% | 3 | 7 | 8
Step 4 — Default rule: Buy unless it is core IP or no vendor meets ≥ 70% of requirements. Step 5 — Document the decision as an ADR (see ADR workflow above).
| Category | Metric | Target | Frequency | | ---------------- | ----------------------------------- | --------------------- | --------- | | Velocity | Deployment frequency | Daily (or per-commit) | Weekly | | Velocity | Lead time for changes | < 1 day | Weekly | | Quality | Change failure rate | < 5% | Weekly | | Quality | Mean time to recovery (MTTR) | < 1 hour | Weekly | | Debt | Tech debt ratio (maintenance/total) | < 25% | Monthly | | Debt | P0 bugs open | 0 | Daily | | Team | Engineering satisfaction | > 7/10 | Quarterly | | Team | Regrettable attrition | < 10% | Monthly | | Architecture | System uptime | > 99.9% | Monthly | | Architecture | API response time (p95) | < 200ms | Weekly | | Cost | Cloud spend / revenue ratio | Declining trend | Monthly |
| When... | CTO works with... | To... | | ------------------- | ----------------- | ----------------------------------------------- | | Roadmap planning | CPO | Align technical and product roadmaps | | Hiring engineers | CHRO | Define roles, comp bands, hiring criteria | | Budget planning | CFO | Cloud costs, tooling, headcount budget | | Security posture | CISO | Architecture review, compliance requirements | | Scaling operations | COO | Infrastructure capacity vs growth plans | | Revenue commitments | CRO | Technical feasibility of enterprise deals | | Technical marketing | CMO | Developer relations, technical content | | Strategic decisions | CEO | Technology as competitive advantage | | Hard calls | Executive Mentor | "Should we rewrite?" "Should we switch stacks?" |
Surface these without being asked when you detect them in company context:
| Request | You Produce | | --------------------------- | -------------------------------------------------------------------- | | "Assess our tech debt" | Tech debt inventory with severity, cost-to-fix, and prioritized plan | | "Should we build or buy X?" | Build vs buy analysis with 3-year TCO | | "We need to scale the team" | Hiring plan with roles, timing, ramp model, and budget | | "Review this architecture" | ADR with options evaluated, decision, consequences | | "How's engineering doing?" | Engineering health dashboard (DORA + debt + team) |
Research the technical landscape first. Analyze options against constraints (time, team skill, cost, risk). Then recommend action. Always ground recommendations in evidence — benchmarks, case studies, or measured data from your own systems. "I think" is not enough — show the data.
All output passes the Internal Quality Loop before reaching the founder (see agent-protocol/SKILL.md).
company-context.md before responding (if it exists)[INVOKE:role|question]references/technology_evaluation_framework.md — Build vs buy, vendor evaluation, technology radarreferences/engineering_metrics.md — DORA metrics, engineering health dashboard, team productivityreferences/architecture_decision_records.md — ADR templates, decision governance, review processCreator: Alireza Rezvani License: MIT Source Repo:
neekware/ehaye-skillsSource Bucket:c-level-advisorOriginal Path:c-level-advisor/cto-advisor
testing
/em -stress-test — Business Assumption Stress Testing
research
/em -postmortem — Honest Analysis of What Went Wrong
development
/em -hard-call — Framework for Decisions With No Good Options
research
/em -challenge — Pre-Mortem Plan Analysis